CodePartB.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "from sklearn.cluster import KMeans\n",
    "from kneed import KneeLocator\n",
    "import collections\n",
    "import auxiliary_functions\n",
    "import pprint\n",
    "import json\n",
    "import random\n",
    "from itertools import combinations\n",
    "from itertools import chain\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from statistics import mean "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset shape: (10000, 13)\n",
      "Query:  ['dist_city=2', 'price=39', 'nbedrooms=3']\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv(\"./data_house/database.csv\", sep = ',') \n",
    "column_names = data.columns\n",
    "n = len(data.columns)\n",
    "print(\"Dataset shape:\", data.shape)\n",
    "\n",
    "# Generate a random query   \n",
    "m = random.randint(2,4)\n",
    "df = data.sample(n = m, axis = 'columns').sample()\n",
    "row = []\n",
    "df_fake_queries = pd.DataFrame(index = range(1), columns = column_names)\n",
    "df_fake_queries.drop(df_fake_queries.columns[df_fake_queries.columns.str.contains('unnamed',case = False)],axis = 1, inplace = True)\n",
    "\n",
    "for j in range(len(df.columns)):\n",
    "    row.append(''.join((str(df.columns[j]),'=',str(df.iloc[0][j]))))\n",
    "    df_fake_queries[str(df.columns[j])].iloc[0] = df.iloc[0][j]\n",
    "\n",
    "print('Query: ', row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>query_id</th>\n",
       "      <th>nrooms</th>\n",
       "      <th>nbedrooms</th>\n",
       "      <th>nbath</th>\n",
       "      <th>sm</th>\n",
       "      <th>garden_sm</th>\n",
       "      <th>floors</th>\n",
       "      <th>gargae_sm</th>\n",
       "      <th>price</th>\n",
       "      <th>year</th>\n",
       "      <th>windows</th>\n",
       "      <th>dist_city</th>\n",
       "      <th>doors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   query_id nrooms nbedrooms nbath   sm garden_sm floors gargae_sm price year  \\\n",
       "0     10000    NaN         3   NaN  NaN       NaN    NaN       NaN    39  NaN   \n",
       "\n",
       "  windows dist_city doors  \n",
       "0     NaN         2   NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = df_fake_queries.dropna(axis = 1)\n",
    "query_columns = query.columns\n",
    "query_values = query.values[0]\n",
    "random_query = df_fake_queries\n",
    "random_query.insert(0,'query_id',10000)\n",
    "random_query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The query does not exist in the database\n"
     ]
    }
   ],
   "source": [
    "# We have to check if the query already exists in our query database\n",
    "queries_temp =  pd.read_csv(\"./data_house/queries_labels.csv\", sep = ',', index_col = 0)\n",
    "queries =  pd.read_csv(\"./data_house/queries_labels.csv\", sep = ',')\n",
    "resData = queries.merge(df_fake_queries, how = 'inner' , on=['nrooms','nbedrooms','nbath','sm','garden_sm','floors','gargae_sm','price','year','windows','dist_city','doors'])\n",
    "if resData.empty:\n",
    "    print('The query does not exist in the database')\n",
    "    case = 1\n",
    "else:\n",
    "    print('The query already exists')\n",
    "    case = 0"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the query exists in the dataframe, we can simply base the importance of that query in the ranking that we have provided in part A. In case it does not exist, we can look for queries with common conditions and find the similarity between these found queries and the top 5 ranked queries for each user."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_queries =  pd.read_csv(\"./data_house/user_queries.csv\", sep = ',')\n",
    "user_queries_fill = pd.read_csv(\"./data_house/user_queries_fill.csv\", sep = ',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "seq = user_queries_fill['user_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = user_queries_fill.iloc[:,2:].values #returns a numpy array\n",
    "min_max_scaler = MinMaxScaler()\n",
    "x_scaled = min_max_scaler.fit_transform(x.transpose())\n",
    "user_queries_fill_minmax = pd.DataFrame(x_scaled.transpose()*100)\n",
    "\n",
    "user_queries_fill_minmax.insert(0,'user_id',seq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['user_id',         0,         1,         2,         3,         4,\n",
       "               5,         6,         7,         8,\n",
       "       ...\n",
       "            1990,      1991,      1992,      1993,      1994,      1995,\n",
       "            1996,      1997,      1998,      1999],\n",
       "      dtype='object', length=2001)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_queries_fill_minmax.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "if case == 0:\n",
    "    importance = pd.DataFrame(0, index = range(len(user_queries)), columns =['user_id','importance_value'])\n",
    "    resData_idx = resData['query_id_x'].tolist()\n",
    "    for i in range(len(user_queries)):\n",
    "        rank = []\n",
    "        for j in range(len(resData_idx)):\n",
    "            rank.append(user_queries_fill_minmax.loc[i,str(j)])\n",
    "            \n",
    "        importance['user_id'].iloc[i] = user_queries['user_id'].iloc[i]\n",
    "        importance['importance_value'].iloc[i] = np.mean(rank)\n",
    "\n",
    "    print(importance[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Case 3: up to 3 common value\n",
      "['nbedrooms', 'nbedrooms', 'nbedrooms', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'price', 'dist_city', 'dist_city']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\elsal\\OneDrive\\Documentos\\Master\\EIT\\Trento\\DataMining\\project\\auxiliary_functions.py:239: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  idx = list(queries[queries[str(query_columns[j])] == query.iloc[0,j]][queries[str(query_columns[i])] == query.iloc[0,i]].index)\n",
      "c:\\Users\\elsal\\OneDrive\\Documentos\\Master\\EIT\\Trento\\DataMining\\project\\auxiliary_functions.py:243: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  idx = list(queries[queries[str(query_columns[0])] == query.iloc[0,0]][queries[str(query_columns[1])] == query.iloc[0,1]][queries[str(query_columns[2])] == query.iloc[0,2]].index)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------user 1------------\n",
      " \n",
      "Top 5 ranked queries:  ['18', '40', '448', '481', '629']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.74, 99.13, 99.04, 99.01]\n",
      "Most similar queries to each of the top ranked:  [1467, 1380, 1380, 1537, 1345]\n",
      "Occurences of the most similar:  [0.33, 0.35, 0.35, 0.3, 0.27]\n",
      "similarity of most similar wrt original query:  [0.06, 0.04, 0.04, 0.03, 0.05]\n",
      "Overall similarity:  [0.04, 0.02, 0.03, 0.02, 0.03]\n",
      "---------------user 2------------\n",
      " \n",
      "Top 5 ranked queries:  ['26', '157', '169', '206', '293']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.56, 98.74, 98.18, 97.44]\n",
      "Most similar queries to each of the top ranked:  [153, 153, 1704, 153, 387]\n",
      "Occurences of the most similar:  [0.37, 0.37, 0.31, 0.37, 0.29]\n",
      "similarity of most similar wrt original query:  [0.04, 0.04, 0.1, 0.04, 0.05]\n",
      "Overall similarity:  [0.02, 0.03, 0.02, 0.02, 0.03]\n",
      "---------------user 3------------\n",
      " \n",
      "Top 5 ranked queries:  ['116', '226', '294', '334', '373']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 92.31, 89.74]\n",
      "Most similar queries to each of the top ranked:  [1051, 638, 1161, 510, 1870]\n",
      "Occurences of the most similar:  [0.33, 0.24, 0.43, 0.29, 0.33]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.4, 0.03, 0.04]\n",
      "Overall similarity:  [0.02, 0.01, 0.25, 0.02, 0.02]\n",
      "---------------user 4------------\n",
      " \n",
      "Top 5 ranked queries:  ['70', '130', '213', '216', '238']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.85, 93.64]\n",
      "Most similar queries to each of the top ranked:  [1362, 402, 1125, 1051, 153]\n",
      "Occurences of the most similar:  [0.21, 0.34, 0.27, 0.33, 0.37]\n",
      "similarity of most similar wrt original query:  [0.07, 0.07, 0.06, 0.04, 0.04]\n",
      "Overall similarity:  [0.05, 0.03, 0.02, 0.03, 0.03]\n",
      "---------------user 5------------\n",
      " \n",
      "Top 5 ranked queries:  ['37', '235', '250', '354', '487']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 94.51, 93.88]\n",
      "Most similar queries to each of the top ranked:  [1362, 407, 747, 178, 153]\n",
      "Occurences of the most similar:  [0.21, 0.29, 0.37, 0.33, 0.37]\n",
      "similarity of most similar wrt original query:  [0.07, 0.7, 0.06, 0.03, 0.04]\n",
      "Overall similarity:  [0.04, 0.32, 0.02, 0.02, 0.02]\n",
      "---------------user 6------------\n",
      " \n",
      "Top 5 ranked queries:  ['138', '1024', '1040', '1157', '1598']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 95.51, 93.88]\n",
      "Most similar queries to each of the top ranked:  [5, 204, 1738, 1648, 1170]\n",
      "Occurences of the most similar:  [0.35, 0.27, 0.3, 0.33, 0.28]\n",
      "similarity of most similar wrt original query:  [0.03, 0.07, 0.06, 0.04, 0.06]\n",
      "Overall similarity:  [0.02, 0.03, 0.02, 0.03, 0.02]\n",
      "---------------user 7------------\n",
      " \n",
      "Top 5 ranked queries:  ['67', '90', '102', '145', '379']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 98.42, 98.0, 97.17]\n",
      "Most similar queries to each of the top ranked:  [583, 812, 204, 1126, 1345]\n",
      "Occurences of the most similar:  [0.36, 0.24, 0.27, 0.31, 0.27]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.07, 0.59, 0.05]\n",
      "Overall similarity:  [0.03, 0.01, 0.03, 0.38, 0.02]\n",
      "---------------user 8------------\n",
      " \n",
      "Top 5 ranked queries:  ['153', '219', '297', '312', '359']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 92.44, 92.31]\n",
      "Most similar queries to each of the top ranked:  [153, 1958, 286, 1958, 359]\n",
      "Occurences of the most similar:  [0.37, 0.3, 0.32, 0.3, 0.3]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.05, 0.06, 0.04]\n",
      "Overall similarity:  [0.04, 0.04, 0.03, 0.02, 0.04]\n",
      "---------------user 9------------\n",
      " \n",
      "Top 5 ranked queries:  ['53', '218', '280', '425', '623']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.26, 97.44, 96.15, 95.23]\n",
      "Most similar queries to each of the top ranked:  [587, 390, 683, 1862, 402]\n",
      "Occurences of the most similar:  [0.29, 0.38, 0.29, 0.24, 0.34]\n",
      "similarity of most similar wrt original query:  [0.05, 0.05, 0.4, 0.05, 0.07]\n",
      "Overall similarity:  [0.04, 0.03, 0.14, 0.03, 0.06]\n",
      "---------------user 10------------\n",
      " \n",
      "Top 5 ranked queries:  ['376', '410', '457', '895', '1197']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 97.21, 95.83, 95.04]\n",
      "Most similar queries to each of the top ranked:  [1624, 1701, 1435, 1545, 562]\n",
      "Occurences of the most similar:  [0.38, 0.31, 0.37, 0.25, 0.34]\n",
      "similarity of most similar wrt original query:  [0.04, 0.1, 0.09, 0.06, 0.06]\n",
      "Overall similarity:  [0.03, 0.04, 0.04, 0.01, 0.04]\n",
      "---------------user 11------------\n",
      " \n",
      "Top 5 ranked queries:  ['472', '480', '633', '675', '812']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 93.88, 93.45]\n",
      "Most similar queries to each of the top ranked:  [402, 204, 683, 153, 812]\n",
      "Occurences of the most similar:  [0.34, 0.27, 0.29, 0.37, 0.24]\n",
      "similarity of most similar wrt original query:  [0.07, 0.07, 0.4, 0.04, 0.06]\n",
      "Overall similarity:  [0.04, 0.04, 0.11, 0.02, 0.06]\n",
      "---------------user 12------------\n",
      " \n",
      "Top 5 ranked queries:  ['404', '501', '872', '1231', '1437']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 97.56, 97.46]\n",
      "Most similar queries to each of the top ranked:  [407, 769, 1545, 1648, 1862]\n",
      "Occurences of the most similar:  [0.29, 0.31, 0.25, 0.33, 0.24]\n",
      "similarity of most similar wrt original query:  [0.7, 0.07, 0.06, 0.04, 0.05]\n",
      "Overall similarity:  [0.5, 0.02, 0.01, 0.04, 0.03]\n",
      "---------------user 13------------\n",
      " \n",
      "Top 5 ranked queries:  ['132', '251', '463', '794', '1290']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.46, 94.36]\n",
      "Most similar queries to each of the top ranked:  [1931, 402, 1230, 402, 1125]\n",
      "Occurences of the most similar:  [0.34, 0.34, 0.31, 0.34, 0.27]\n",
      "similarity of most similar wrt original query:  [0.06, 0.07, 0.06, 0.07, 0.06]\n",
      "Overall similarity:  [0.03, 0.03, 0.03, 0.04, 0.04]\n",
      "---------------user 14------------\n",
      " \n",
      "Top 5 ranked queries:  ['55', '218', '280', '311', '364']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 95.03, 94.87, 94.69]\n",
      "Most similar queries to each of the top ranked:  [812, 390, 683, 117, 402]\n",
      "Occurences of the most similar:  [0.24, 0.38, 0.29, 0.33, 0.34]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.4, 0.05, 0.07]\n",
      "Overall similarity:  [0.03, 0.03, 0.14, 0.03, 0.03]\n",
      "---------------user 15------------\n",
      " \n",
      "Top 5 ranked queries:  ['114', '356', '909', '1812', '1924']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.1, 95.65, 95.62]\n",
      "Most similar queries to each of the top ranked:  [1669, 1983, 431, 1704, 1096]\n",
      "Occurences of the most similar:  [0.34, 0.24, 0.28, 0.31, 0.31]\n",
      "similarity of most similar wrt original query:  [0.06, 0.03, 0.8, 0.1, 0.06]\n",
      "Overall similarity:  [0.04, 0.02, 0.36, 0.03, 0.03]\n",
      "---------------user 16------------\n",
      " \n",
      "Top 5 ranked queries:  ['195', '451', '703', '835', '1210']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.05, 93.69]\n",
      "Most similar queries to each of the top ranked:  [1545, 286, 120, 153, 1635]\n",
      "Occurences of the most similar:  [0.25, 0.32, 0.32, 0.37, 0.33]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.06, 0.04, 0.06]\n",
      "Overall similarity:  [0.01, 0.01, 0.03, 0.03, 0.01]\n",
      "---------------user 17------------\n",
      " \n",
      "Top 5 ranked queries:  ['40', '51', '102', '141', '281']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 97.24, 95.92, 94.65]\n",
      "Most similar queries to each of the top ranked:  [1380, 873, 204, 1624, 882]\n",
      "Occurences of the most similar:  [0.35, 0.35, 0.27, 0.38, 0.34]\n",
      "similarity of most similar wrt original query:  [0.04, 0.07, 0.07, 0.04, 0.05]\n",
      "Overall similarity:  [0.02, 0.04, 0.03, 0.02, 0.03]\n",
      "---------------user 18------------\n",
      " \n",
      "Top 5 ranked queries:  ['161', '162', '430', '583', '761']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 97.21, 97.0, 96.54]\n",
      "Most similar queries to each of the top ranked:  [1035, 1780, 608, 583, 1986]\n",
      "Occurences of the most similar:  [0.29, 0.31, 0.31, 0.36, 0.34]\n",
      "similarity of most similar wrt original query:  [0.05, 0.1, 0.71, 0.04, 0.07]\n",
      "Overall similarity:  [0.05, 0.03, 0.61, 0.04, 0.02]\n",
      "---------------user 19------------\n",
      " \n",
      "Top 5 ranked queries:  ['1', '12', '35', '99', '164']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.46, 99.27, 99.23, 99.0]\n",
      "Most similar queries to each of the top ranked:  [1545, 882, 812, 1230, 153]\n",
      "Occurences of the most similar:  [0.25, 0.34, 0.24, 0.31, 0.37]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.06, 0.06, 0.04]\n",
      "Overall similarity:  [0.02, 0.03, 0.01, 0.02, 0.03]\n",
      "---------------user 20------------\n",
      " \n",
      "Top 5 ranked queries:  ['26', '35', '154', '211', '248']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.23, 93.0]\n",
      "Most similar queries to each of the top ranked:  [153, 812, 1545, 1096, 1588]\n",
      "Occurences of the most similar:  [0.37, 0.24, 0.25, 0.31, 0.41]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.06, 0.05]\n",
      "Overall similarity:  [0.02, 0.01, 0.03, 0.02, 0.04]\n",
      "---------------user 21------------\n",
      " \n",
      "Top 5 ranked queries:  ['104', '192', '407', '814', '1128']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 97.27, 95.83, 95.67]\n",
      "Most similar queries to each of the top ranked:  [153, 402, 1128, 709, 1128]\n",
      "Occurences of the most similar:  [0.37, 0.34, 0.23, 0.4, 0.23]\n",
      "similarity of most similar wrt original query:  [0.04, 0.07, 0.86, 0.04, 0.86]\n",
      "Overall similarity:  [0.02, 0.05, 0.56, 0.03, 0.86]\n",
      "---------------user 22------------\n",
      " \n",
      "Top 5 ranked queries:  ['10', '117', '135', '165', '181']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 93.51, 92.74]\n",
      "Most similar queries to each of the top ranked:  [402, 1345, 387, 1983, 108]\n",
      "Occurences of the most similar:  [0.34, 0.27, 0.29, 0.24, 0.26]\n",
      "similarity of most similar wrt original query:  [0.07, 0.05, 0.05, 0.03, 0.07]\n",
      "Overall similarity:  [0.04, 0.03, 0.02, 0.02, 0.03]\n",
      "---------------user 23------------\n",
      " \n",
      "Top 5 ranked queries:  ['33', '115', '141', '281', '300']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.46, 97.51, 97.44, 96.23]\n",
      "Most similar queries to each of the top ranked:  [1035, 1773, 1624, 882, 407]\n",
      "Occurences of the most similar:  [0.29, 0.32, 0.38, 0.34, 0.29]\n",
      "similarity of most similar wrt original query:  [0.05, 0.05, 0.04, 0.05, 0.7]\n",
      "Overall similarity:  [0.04, 0.02, 0.02, 0.03, 0.17]\n",
      "---------------user 24------------\n",
      " \n",
      "Top 5 ranked queries:  ['202', '256', '863', '993', '1155']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 93.88, 92.24]\n",
      "Most similar queries to each of the top ranked:  [709, 638, 812, 153, 1051]\n",
      "Occurences of the most similar:  [0.4, 0.24, 0.24, 0.37, 0.33]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.04, 0.04]\n",
      "Overall similarity:  [0.03, 0.03, 0.01, 0.02, 0.02]\n",
      "---------------user 25------------\n",
      " \n",
      "Top 5 ranked queries:  ['17', '94', '175', '215', '521']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.59, 99.51, 99.12, 98.92]\n",
      "Most similar queries to each of the top ranked:  [402, 286, 583, 926, 1958]\n",
      "Occurences of the most similar:  [0.34, 0.32, 0.36, 0.37, 0.3]\n",
      "similarity of most similar wrt original query:  [0.07, 0.05, 0.04, 0.04, 0.06]\n",
      "Overall similarity:  [0.04, 0.01, 0.02, 0.03, 0.03]\n",
      "---------------user 26------------\n",
      " \n",
      "Top 5 ranked queries:  ['1043', '1080', '1193', '1342', '1358']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.1, 95.65, 94.2]\n",
      "Most similar queries to each of the top ranked:  [1701, 153, 873, 407, 873]\n",
      "Occurences of the most similar:  [0.31, 0.37, 0.35, 0.29, 0.35]\n",
      "similarity of most similar wrt original query:  [0.1, 0.04, 0.07, 0.7, 0.07]\n",
      "Overall similarity:  [0.06, 0.02, 0.04, 0.31, 0.03]\n",
      "---------------user 27------------\n",
      " \n",
      "Top 5 ranked queries:  ['137', '256', '655', '918', '927']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 97.31, 96.38, 95.82]\n",
      "Most similar queries to each of the top ranked:  [1545, 638, 1435, 764, 1635]\n",
      "Occurences of the most similar:  [0.25, 0.24, 0.37, 0.33, 0.33]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.09, 0.5, 0.06]\n",
      "Overall similarity:  [0.02, 0.03, 0.04, 0.17, 0.03]\n",
      "---------------user 28------------\n",
      " \n",
      "Top 5 ranked queries:  ['6', '37', '416', '511', '565']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.71, 98.55, 98.04, 97.1]\n",
      "Most similar queries to each of the top ranked:  [407, 1362, 608, 812, 565]\n",
      "Occurences of the most similar:  [0.29, 0.21, 0.31, 0.24, 0.27]\n",
      "similarity of most similar wrt original query:  [0.7, 0.07, 0.71, 0.06, 0.05]\n",
      "Overall similarity:  [0.15, 0.04, 0.5, 0.04, 0.05]\n",
      "---------------user 29------------\n",
      " \n",
      "Top 5 ranked queries:  ['93', '139', '246', '324', '424']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 94.2, 93.88]\n",
      "Most similar queries to each of the top ranked:  [108, 1958, 1096, 1701, 1958]\n",
      "Occurences of the most similar:  [0.26, 0.3, 0.31, 0.31, 0.3]\n",
      "similarity of most similar wrt original query:  [0.07, 0.06, 0.06, 0.1, 0.06]\n",
      "Overall similarity:  [0.03, 0.03, 0.02, 0.06, 0.02]\n",
      "---------------user 30------------\n",
      " \n",
      "Top 5 ranked queries:  ['161', '577', '587', '906', '950']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 96.62, 96.5, 96.44]\n",
      "Most similar queries to each of the top ranked:  [1035, 769, 587, 402, 784]\n",
      "Occurences of the most similar:  [0.29, 0.31, 0.29, 0.34, 0.23]\n",
      "similarity of most similar wrt original query:  [0.05, 0.07, 0.05, 0.07, 0.04]\n",
      "Overall similarity:  [0.05, 0.02, 0.05, 0.06, 0.02]\n",
      "---------------user 31------------\n",
      " \n",
      "Top 5 ranked queries:  ['119', '641', '739', '889', '1027']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 93.88, 91.84]\n",
      "Most similar queries to each of the top ranked:  [1230, 1506, 1862, 434, 1773]\n",
      "Occurences of the most similar:  [0.31, 0.24, 0.24, 0.2, 0.32]\n",
      "similarity of most similar wrt original query:  [0.06, 0.09, 0.05, 0.8, 0.05]\n",
      "Overall similarity:  [0.02, 0.04, 0.03, 0.64, 0.02]\n",
      "---------------user 32------------\n",
      " \n",
      "Top 5 ranked queries:  ['22', '28', '160', '230', '250']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.59, 96.44, 95.69]\n",
      "Most similar queries to each of the top ranked:  [1701, 1125, 1126, 818, 747]\n",
      "Occurences of the most similar:  [0.31, 0.27, 0.31, 0.31, 0.37]\n",
      "similarity of most similar wrt original query:  [0.1, 0.06, 0.59, 0.53, 0.06]\n",
      "Overall similarity:  [0.04, 0.03, 0.37, 0.28, 0.02]\n",
      "---------------user 33------------\n",
      " \n",
      "Top 5 ranked queries:  ['72', '102', '115', '175', '183']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 96.06]\n",
      "Most similar queries to each of the top ranked:  [1048, 204, 1773, 583, 204]\n",
      "Occurences of the most similar:  [0.46, 0.27, 0.32, 0.36, 0.27]\n",
      "similarity of most similar wrt original query:  [0.07, 0.07, 0.05, 0.04, 0.07]\n",
      "Overall similarity:  [0.06, 0.03, 0.02, 0.02, 0.03]\n",
      "---------------user 34------------\n",
      " \n",
      "Top 5 ranked queries:  ['253', '284', '306', '345', '352']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 97.71, 97.33, 96.61]\n",
      "Most similar queries to each of the top ranked:  [153, 773, 812, 23, 608]\n",
      "Occurences of the most similar:  [0.37, 0.3, 0.24, 0.34, 0.31]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.8, 0.71]\n",
      "Overall similarity:  [0.03, 0.04, 0.03, 0.64, 0.51]\n",
      "---------------user 35------------\n",
      " \n",
      "Top 5 ranked queries:  ['281', '315', '459', '581', '675']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 96.52, 95.83, 93.75]\n",
      "Most similar queries to each of the top ranked:  [882, 402, 812, 1125, 153]\n",
      "Occurences of the most similar:  [0.34, 0.34, 0.24, 0.27, 0.37]\n",
      "similarity of most similar wrt original query:  [0.05, 0.07, 0.06, 0.06, 0.04]\n",
      "Overall similarity:  [0.03, 0.05, 0.02, 0.03, 0.02]\n",
      "---------------user 36------------\n",
      " \n",
      "Top 5 ranked queries:  ['22', '23', '95', '121', '164']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.97, 98.87, 97.51, 97.44]\n",
      "Most similar queries to each of the top ranked:  [1701, 407, 812, 1701, 153]\n",
      "Occurences of the most similar:  [0.31, 0.29, 0.24, 0.31, 0.37]\n",
      "similarity of most similar wrt original query:  [0.1, 0.7, 0.06, 0.1, 0.04]\n",
      "Overall similarity:  [0.04, 0.51, 0.03, 0.05, 0.03]\n",
      "---------------user 37------------\n",
      " \n",
      "Top 5 ranked queries:  ['166', '232', '296', '329', '382']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.59, 93.26]\n",
      "Most similar queries to each of the top ranked:  [1380, 1069, 764, 1048, 359]\n",
      "Occurences of the most similar:  [0.35, 0.33, 0.33, 0.46, 0.3]\n",
      "similarity of most similar wrt original query:  [0.04, 0.05, 0.5, 0.07, 0.04]\n",
      "Overall similarity:  [0.02, 0.03, 0.27, 0.05, 0.01]\n",
      "---------------user 38------------\n",
      " \n",
      "Top 5 ranked queries:  ['1228', '1910', '8', '22', '101']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.1, 95.65, 95.59]\n",
      "Most similar queries to each of the top ranked:  [153, 1402, 1096, 1701, 1545]\n",
      "Occurences of the most similar:  [0.37, 0.3, 0.31, 0.31, 0.25]\n",
      "similarity of most similar wrt original query:  [0.04, 0.57, 0.06, 0.1, 0.06]\n",
      "Overall similarity:  [0.02, 0.46, 0.04, 0.04, 0.01]\n",
      "---------------user 39------------\n",
      " \n",
      "Top 5 ranked queries:  ['65', '68', '92', '204', '250']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.0, 98.72, 98.13, 97.79]\n",
      "Most similar queries to each of the top ranked:  [1380, 773, 402, 1669, 747]\n",
      "Occurences of the most similar:  [0.35, 0.3, 0.34, 0.34, 0.37]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.07, 0.06, 0.06]\n",
      "Overall similarity:  [0.03, 0.03, 0.04, 0.02, 0.02]\n",
      "---------------user 40------------\n",
      " \n",
      "Top 5 ranked queries:  ['13', '48', '74', '88', '100']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.13, 95.33, 95.31]\n",
      "Most similar queries to each of the top ranked:  [1230, 48, 1362, 562, 1566]\n",
      "Occurences of the most similar:  [0.31, 0.39, 0.21, 0.34, 0.44]\n",
      "similarity of most similar wrt original query:  [0.06, 0.07, 0.07, 0.06, 0.03]\n",
      "Overall similarity:  [0.03, 0.07, 0.05, 0.04, 0.02]\n",
      "---------------user 41------------\n",
      " \n",
      "Top 5 ranked queries:  ['195', '695', '872', '1131', '1624']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.35, 98.98, 98.26, 97.96]\n",
      "Most similar queries to each of the top ranked:  [1545, 1345, 1545, 434, 926]\n",
      "Occurences of the most similar:  [0.25, 0.27, 0.25, 0.2, 0.37]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.06, 0.8, 0.04]\n",
      "Overall similarity:  [0.01, 0.01, 0.01, 0.56, 0.03]\n",
      "---------------user 42------------\n",
      " \n",
      "Top 5 ranked queries:  ['289', '870', '871', '908', '916']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 96.37, 96.35, 95.83]\n",
      "Most similar queries to each of the top ranked:  [873, 117, 1669, 25, 402]\n",
      "Occurences of the most similar:  [0.35, 0.33, 0.34, 0.28, 0.34]\n",
      "similarity of most similar wrt original query:  [0.07, 0.05, 0.06, 0.03, 0.07]\n",
      "Overall similarity:  [0.04, 0.02, 0.04, 0.01, 0.04]\n",
      "---------------user 43------------\n",
      " \n",
      "Top 5 ranked queries:  ['78', '194', '301', '439', '713']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.97, 96.46, 96.28]\n",
      "Most similar queries to each of the top ranked:  [1402, 608, 1152, 1669, 434]\n",
      "Occurences of the most similar:  [0.3, 0.31, 0.34, 0.34, 0.2]\n",
      "similarity of most similar wrt original query:  [0.57, 0.71, 0.04, 0.06, 0.8]\n",
      "Overall similarity:  [0.43, 0.43, 0.03, 0.03, 0.7]\n",
      "---------------user 44------------\n",
      " \n",
      "Top 5 ranked queries:  ['12', '35', '69', '99', '109']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.92, 99.9, 99.79, 99.74]\n",
      "Most similar queries to each of the top ranked:  [882, 812, 182, 1230, 1931]\n",
      "Occurences of the most similar:  [0.34, 0.24, 0.31, 0.31, 0.34]\n",
      "similarity of most similar wrt original query:  [0.05, 0.06, 0.05, 0.06, 0.06]\n",
      "Overall similarity:  [0.03, 0.01, 0.02, 0.02, 0.02]\n",
      "---------------user 45------------\n",
      " \n",
      "Top 5 ranked queries:  ['113', '219', '401', '639', '877']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 93.88, 93.39]\n",
      "Most similar queries to each of the top ranked:  [1545, 1958, 1648, 882, 431]\n",
      "Occurences of the most similar:  [0.25, 0.3, 0.33, 0.34, 0.28]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.04, 0.05, 0.8]\n",
      "Overall similarity:  [0.01, 0.04, 0.03, 0.02, 0.4]\n",
      "---------------user 46------------\n",
      " \n",
      "Top 5 ranked queries:  ['378', '1570', '1975', '88', '233']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 94.5, 93.75]\n",
      "Most similar queries to each of the top ranked:  [1773, 1983, 1096, 562, 1545]\n",
      "Occurences of the most similar:  [0.32, 0.24, 0.31, 0.34, 0.25]\n",
      "similarity of most similar wrt original query:  [0.05, 0.03, 0.06, 0.06, 0.06]\n",
      "Overall similarity:  [0.01, 0.02, 0.03, 0.04, 0.01]\n",
      "---------------user 47------------\n",
      " \n",
      "Top 5 ranked queries:  ['38', '63', '92', '123', '150']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.86, 99.12, 98.94, 98.92]\n",
      "Most similar queries to each of the top ranked:  [1545, 407, 402, 1467, 954]\n",
      "Occurences of the most similar:  [0.25, 0.29, 0.34, 0.33, 0.38]\n",
      "similarity of most similar wrt original query:  [0.06, 0.7, 0.07, 0.06, 0.05]\n",
      "Overall similarity:  [0.01, 0.46, 0.04, 0.05, 0.03]\n",
      "---------------user 48------------\n",
      " \n",
      "Top 5 ranked queries:  ['174', '251', '395', '428', '585']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 94.0, 93.88]\n",
      "Most similar queries to each of the top ranked:  [1506, 402, 431, 1983, 644]\n",
      "Occurences of the most similar:  [0.24, 0.34, 0.28, 0.24, 0.39]\n",
      "similarity of most similar wrt original query:  [0.09, 0.07, 0.8, 0.03, 0.05]\n",
      "Overall similarity:  [0.04, 0.03, 0.73, 0.03, 0.02]\n",
      "---------------user 49------------\n",
      " \n",
      "Top 5 ranked queries:  ['407', '431', '578', '613', '795']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [1128, 110, 1444, 1648, 1958]\n",
      "Occurences of the most similar:  [0.23, 0.34, 0.26, 0.33, 0.3]\n",
      "similarity of most similar wrt original query:  [0.86, 0.66, 0.14, 0.04, 0.06]\n",
      "Overall similarity:  [0.56, 0.53, 0.05, 0.04, 0.03]\n",
      "---------------user 50------------\n",
      " \n",
      "Top 5 ranked queries:  ['1232', '1296', '1672', '81', '1460']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [1704, 1128, 1701, 120, 108]\n",
      "Occurences of the most similar:  [0.31, 0.23, 0.31, 0.32, 0.26]\n",
      "similarity of most similar wrt original query:  [0.1, 0.86, 0.1, 0.06, 0.07]\n",
      "Overall similarity:  [0.04, 0.61, 0.08, 0.02, 0.02]\n",
      "---------------user 51------------\n",
      " \n",
      "Top 5 ranked queries:  ['1385', '1483', '1694', '1812', '1973']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [117, 1345, 1402, 1704, 1862]\n",
      "Occurences of the most similar:  [0.33, 0.27, 0.3, 0.31, 0.24]\n",
      "similarity of most similar wrt original query:  [0.05, 0.05, 0.57, 0.1, 0.05]\n",
      "Overall similarity:  [0.03, 0.02, 0.42, 0.03, 0.03]\n",
      "---------------user 52------------\n",
      " \n",
      "Top 5 ranked queries:  ['1519', '1812', '171', '479', '1749']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [773, 1704, 1435, 562, 1624]\n",
      "Occurences of the most similar:  [0.3, 0.31, 0.37, 0.34, 0.38]\n",
      "similarity of most similar wrt original query:  [0.06, 0.1, 0.09, 0.06, 0.04]\n",
      "Overall similarity:  [0.02, 0.03, 0.03, 0.03, 0.02]\n",
      "---------------user 53------------\n",
      " \n",
      "Top 5 ranked queries:  ['21', '40', '194', '359', '502']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.63, 97.96, 96.29, 95.92]\n",
      "Most similar queries to each of the top ranked:  [943, 1380, 608, 359, 873]\n",
      "Occurences of the most similar:  [0.28, 0.35, 0.31, 0.3, 0.35]\n",
      "similarity of most similar wrt original query:  [0.07, 0.04, 0.71, 0.04, 0.07]\n",
      "Overall similarity:  [0.03, 0.02, 0.43, 0.04, 0.02]\n",
      "---------------user 54------------\n",
      " \n",
      "Top 5 ranked queries:  ['9', '28', '67', '71', '79']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.26, 97.97, 97.92, 97.54]\n",
      "Most similar queries to each of the top ranked:  [764, 1125, 583, 120, 1128]\n",
      "Occurences of the most similar:  [0.33, 0.27, 0.36, 0.32, 0.23]\n",
      "similarity of most similar wrt original query:  [0.5, 0.06, 0.04, 0.06, 0.86]\n",
      "Overall similarity:  [0.29, 0.03, 0.03, 0.03, 0.73]\n",
      "---------------user 55------------\n",
      " \n",
      "Top 5 ranked queries:  ['58', '105', '157', '331', '385']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.95, 98.51, 98.05, 97.95]\n",
      "Most similar queries to each of the top ranked:  [390, 1509, 153, 747, 1362]\n",
      "Occurences of the most similar:  [0.38, 0.29, 0.37, 0.37, 0.21]\n",
      "similarity of most similar wrt original query:  [0.05, 0.09, 0.04, 0.06, 0.07]\n",
      "Overall similarity:  [0.03, 0.07, 0.03, 0.02, 0.04]\n",
      "---------------user 56------------\n",
      " \n",
      "Top 5 ranked queries:  ['1398', '1743', '1750', '236', '995']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [873, 1161, 1128, 1051, 1362]\n",
      "Occurences of the most similar:  [0.35, 0.43, 0.23, 0.33, 0.21]\n",
      "similarity of most similar wrt original query:  [0.07, 0.4, 0.86, 0.04, 0.07]\n",
      "Overall similarity:  [0.04, 0.26, 0.63, 0.01, 0.03]\n",
      "---------------user 57------------\n",
      " \n",
      "Top 5 ranked queries:  ['141', '142', '150', '281', '286']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.59, 98.82, 97.69, 97.44]\n",
      "Most similar queries to each of the top ranked:  [1624, 638, 954, 882, 286]\n",
      "Occurences of the most similar:  [0.38, 0.24, 0.38, 0.34, 0.32]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.05, 0.05, 0.05]\n",
      "Overall similarity:  [0.02, 0.01, 0.03, 0.03, 0.05]\n",
      "---------------user 58------------\n",
      " \n",
      "Top 5 ranked queries:  ['2', '38', '99', '156', '158']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.18, 99.15, 98.87, 98.59]\n",
      "Most similar queries to each of the top ranked:  [153, 1545, 1230, 1051, 1035]\n",
      "Occurences of the most similar:  [0.37, 0.25, 0.31, 0.33, 0.29]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.04, 0.05]\n",
      "Overall similarity:  [0.02, 0.01, 0.02, 0.03, 0.04]\n",
      "---------------user 59------------\n",
      " \n",
      "Top 5 ranked queries:  ['147', '170', '214', '267', '372']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.72, 99.62, 99.33, 99.31]\n",
      "Most similar queries to each of the top ranked:  [1648, 407, 120, 613, 120]\n",
      "Occurences of the most similar:  [0.33, 0.29, 0.32, 0.41, 0.32]\n",
      "similarity of most similar wrt original query:  [0.04, 0.7, 0.06, 0.04, 0.06]\n",
      "Overall similarity:  [0.03, 0.42, 0.02, 0.03, 0.03]\n",
      "---------------user 60------------\n",
      " \n",
      "Top 5 ranked queries:  ['342', '599', '647', '687', '775']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 92.31, 89.74]\n",
      "Most similar queries to each of the top ranked:  [1870, 1293, 873, 407, 1773]\n",
      "Occurences of the most similar:  [0.33, 0.32, 0.35, 0.29, 0.32]\n",
      "similarity of most similar wrt original query:  [0.04, 0.03, 0.07, 0.7, 0.05]\n",
      "Overall similarity:  [0.03, 0.02, 0.03, 0.34, 0.03]\n",
      "---------------user 61------------\n",
      " \n",
      "Top 5 ranked queries:  ['14', '58', '74', '123', '256']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.67, 99.58, 99.04, 98.9]\n",
      "Most similar queries to each of the top ranked:  [1031, 390, 1362, 1467, 638]\n",
      "Occurences of the most similar:  [0.29, 0.38, 0.21, 0.33, 0.24]\n",
      "similarity of most similar wrt original query:  [0.05, 0.05, 0.07, 0.06, 0.06]\n",
      "Overall similarity:  [0.01, 0.03, 0.05, 0.05, 0.03]\n",
      "---------------user 62------------\n",
      " \n",
      "Top 5 ranked queries:  ['368', '532', '703', '1196', '1246']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.46, 95.54, 95.21]\n",
      "Most similar queries to each of the top ranked:  [562, 1624, 120, 587, 1152]\n",
      "Occurences of the most similar:  [0.34, 0.38, 0.32, 0.29, 0.34]\n",
      "similarity of most similar wrt original query:  [0.06, 0.04, 0.06, 0.05, 0.04]\n",
      "Overall similarity:  [0.03, 0.02, 0.03, 0.03, 0.03]\n",
      "---------------user 63------------\n",
      " \n",
      "Top 5 ranked queries:  ['416', '580', '716', '844', '896']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.1, 95.65, 94.2]\n",
      "Most similar queries to each of the top ranked:  [608, 1170, 407, 1701, 390]\n",
      "Occurences of the most similar:  [0.31, 0.28, 0.29, 0.31, 0.38]\n",
      "similarity of most similar wrt original query:  [0.71, 0.06, 0.7, 0.1, 0.05]\n",
      "Overall similarity:  [0.5, 0.01, 0.2, 0.04, 0.02]\n",
      "---------------user 64------------\n",
      " \n",
      "Top 5 ranked queries:  ['412', '827', '878', '964', '1351']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 93.56, 92.77]\n",
      "Most similar queries to each of the top ranked:  [1506, 23, 764, 403, 1170]\n",
      "Occurences of the most similar:  [0.24, 0.34, 0.33, 0.27, 0.28]\n",
      "similarity of most similar wrt original query:  [0.09, 0.8, 0.5, 0.34, 0.06]\n",
      "Overall similarity:  [0.03, 0.62, 0.34, 0.14, 0.03]\n",
      "---------------user 65------------\n",
      " \n",
      "Top 5 ranked queries:  ['530', '696', '704', '826', '887']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [431, 1048, 1545, 1362, 182]\n",
      "Occurences of the most similar:  [0.28, 0.46, 0.25, 0.21, 0.31]\n",
      "similarity of most similar wrt original query:  [0.8, 0.07, 0.06, 0.07, 0.05]\n",
      "Overall similarity:  [0.64, 0.05, 0.01, 0.04, 0.04]\n",
      "---------------user 66------------\n",
      " \n",
      "Top 5 ranked queries:  ['695', '859', '1283', '14', '180']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [1345, 769, 402, 1031, 1545]\n",
      "Occurences of the most similar:  [0.27, 0.31, 0.34, 0.29, 0.25]\n",
      "similarity of most similar wrt original query:  [0.05, 0.07, 0.07, 0.05, 0.06]\n",
      "Overall similarity:  [0.01, 0.02, 0.05, 0.01, 0.01]\n",
      "---------------user 67------------\n",
      " \n",
      "Top 5 ranked queries:  ['27', '42', '161', '212', '348']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.54, 97.44, 96.33, 96.15]\n",
      "Most similar queries to each of the top ranked:  [1738, 442, 1035, 1506, 1230]\n",
      "Occurences of the most similar:  [0.3, 0.26, 0.29, 0.24, 0.31]\n",
      "similarity of most similar wrt original query:  [0.06, 0.07, 0.05, 0.09, 0.06]\n",
      "Overall similarity:  [0.02, 0.03, 0.05, 0.04, 0.01]\n",
      "---------------user 68------------\n",
      " \n",
      "Top 5 ranked queries:  ['85', '195', '258', '322', '331']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.49, 97.44, 94.87, 94.13]\n",
      "Most similar queries to each of the top ranked:  [1051, 1545, 1230, 1031, 747]\n",
      "Occurences of the most similar:  [0.33, 0.25, 0.31, 0.29, 0.37]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.05, 0.06]\n",
      "Overall similarity:  [0.03, 0.01, 0.03, 0.02, 0.02]\n",
      "---------------user 69------------\n",
      " \n",
      "Top 5 ranked queries:  ['334', '415', '720', '737', '868']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 92.31, 92.0]\n",
      "Most similar queries to each of the top ranked:  [510, 422, 1545, 407, 1052]\n",
      "Occurences of the most similar:  [0.29, 0.31, 0.25, 0.29, 0.38]\n",
      "similarity of most similar wrt original query:  [0.03, 0.05, 0.06, 0.7, 0.08]\n",
      "Overall similarity:  [0.02, 0.04, 0.04, 0.45, 0.06]\n",
      "---------------user 70------------\n",
      " \n",
      "Top 5 ranked queries:  ['644', '827', '833', '1171', '1244']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 95.54, 95.29]\n",
      "Most similar queries to each of the top ranked:  [285, 23, 1958, 1983, 1738]\n",
      "Occurences of the most similar:  [0.34, 0.34, 0.3, 0.24, 0.3]\n",
      "similarity of most similar wrt original query:  [0.05, 0.8, 0.06, 0.03, 0.06]\n",
      "Overall similarity:  [0.05, 0.62, 0.03, 0.01, 0.02]\n",
      "---------------user 71------------\n",
      " \n",
      "Top 5 ranked queries:  ['23', '170', '218', '254', '352']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.81, 98.12, 97.92, 97.46]\n",
      "Most similar queries to each of the top ranked:  [407, 407, 390, 1457, 608]\n",
      "Occurences of the most similar:  [0.29, 0.29, 0.38, 0.31, 0.31]\n",
      "similarity of most similar wrt original query:  [0.7, 0.7, 0.05, 0.05, 0.71]\n",
      "Overall similarity:  [0.51, 0.42, 0.03, 0.04, 0.51]\n",
      "---------------user 72------------\n",
      " \n",
      "Top 5 ranked queries:  ['19', '226', '236', '357', '386']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 97.54, 97.5, 97.48]\n",
      "Most similar queries to each of the top ranked:  [1931, 638, 1051, 1069, 1958]\n",
      "Occurences of the most similar:  [0.34, 0.24, 0.33, 0.33, 0.3]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.04, 0.05, 0.06]\n",
      "Overall similarity:  [0.02, 0.01, 0.01, 0.03, 0.03]\n",
      "---------------user 73------------\n",
      " \n",
      "Top 5 ranked queries:  ['60', '86', '92', '204', '239']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 99.38, 98.62, 98.59, 98.0]\n",
      "Most similar queries to each of the top ranked:  [82, 1540, 402, 1669, 1380]\n",
      "Occurences of the most similar:  [0.4, 0.32, 0.34, 0.34, 0.35]\n",
      "similarity of most similar wrt original query:  [0.05, 0.02, 0.07, 0.06, 0.04]\n",
      "Overall similarity:  [0.03, 0.01, 0.04, 0.02, 0.03]\n",
      "---------------user 74------------\n",
      " \n",
      "Top 5 ranked queries:  ['43', '509', '529', '708', '779']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.28, 95.82, 94.87]\n",
      "Most similar queries to each of the top ranked:  [1152, 120, 812, 1537, 402]\n",
      "Occurences of the most similar:  [0.34, 0.32, 0.24, 0.3, 0.34]\n",
      "similarity of most similar wrt original query:  [0.04, 0.06, 0.06, 0.03, 0.07]\n",
      "Overall similarity:  [0.03, 0.03, 0.03, 0.02, 0.04]\n",
      "---------------user 75------------\n",
      " \n",
      "Top 5 ranked queries:  ['74', '743', '983', '1055', '1084']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.1, 95.65, 94.2]\n",
      "Most similar queries to each of the top ranked:  [1362, 1773, 1983, 812, 48]\n",
      "Occurences of the most similar:  [0.21, 0.32, 0.24, 0.24, 0.39]\n",
      "similarity of most similar wrt original query:  [0.07, 0.05, 0.03, 0.06, 0.07]\n",
      "Overall similarity:  [0.05, 0.03, 0.02, 0.02, 0.02]\n",
      "---------------user 76------------\n",
      " \n",
      "Top 5 ranked queries:  ['22', '131', '139', '165', '267']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.95, 97.67, 97.44, 97.26]\n",
      "Most similar queries to each of the top ranked:  [1701, 954, 1958, 1983, 613]\n",
      "Occurences of the most similar:  [0.31, 0.38, 0.3, 0.24, 0.41]\n",
      "similarity of most similar wrt original query:  [0.1, 0.05, 0.06, 0.03, 0.04]\n",
      "Overall similarity:  [0.04, 0.02, 0.03, 0.02, 0.03]\n",
      "---------------user 77------------\n",
      " \n",
      "Top 5 ranked queries:  ['27', '93', '99', '163', '384']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.97, 97.9, 97.44, 96.05]\n",
      "Most similar queries to each of the top ranked:  [1738, 108, 1230, 943, 1035]\n",
      "Occurences of the most similar:  [0.3, 0.26, 0.31, 0.28, 0.29]\n",
      "similarity of most similar wrt original query:  [0.06, 0.07, 0.06, 0.07, 0.05]\n",
      "Overall similarity:  [0.02, 0.03, 0.02, 0.04, 0.04]\n",
      "---------------user 78------------\n",
      " \n",
      "Top 5 ranked queries:  ['120', '247', '377', '670', '754']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 97.8, 97.67, 97.43]\n",
      "Most similar queries to each of the top ranked:  [911, 1738, 1096, 1457, 108]\n",
      "Occurences of the most similar:  [0.32, 0.3, 0.31, 0.31, 0.26]\n",
      "similarity of most similar wrt original query:  [0.05, 0.06, 0.06, 0.05, 0.07]\n",
      "Overall similarity:  [0.03, 0.02, 0.04, 0.03, 0.02]\n",
      "---------------user 79------------\n",
      " \n",
      "Top 5 ranked queries:  ['803', '984', '1445', '1758', '162']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [178, 120, 387, 1230, 1780]\n",
      "Occurences of the most similar:  [0.33, 0.32, 0.29, 0.31, 0.31]\n",
      "similarity of most similar wrt original query:  [0.03, 0.06, 0.05, 0.06, 0.1]\n",
      "Overall similarity:  [0.02, 0.03, 0.03, 0.02, 0.03]\n",
      "---------------user 80------------\n",
      " \n",
      "Top 5 ranked queries:  ['89', '193', '229', '268', '388']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 95.97, 94.87, 94.1]\n",
      "Most similar queries to each of the top ranked:  [431, 48, 407, 1701, 954]\n",
      "Occurences of the most similar:  [0.28, 0.39, 0.29, 0.31, 0.38]\n",
      "similarity of most similar wrt original query:  [0.8, 0.07, 0.7, 0.1, 0.05]\n",
      "Overall similarity:  [0.29, 0.07, 0.13, 0.03, 0.03]\n",
      "---------------user 81------------\n",
      " \n",
      "Top 5 ranked queries:  ['28', '111', '119', '257', '492']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.33, 95.74, 95.38]\n",
      "Most similar queries to each of the top ranked:  [1125, 954, 1230, 812, 873]\n",
      "Occurences of the most similar:  [0.27, 0.38, 0.31, 0.24, 0.35]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.06, 0.06, 0.07]\n",
      "Overall similarity:  [0.03, 0.02, 0.02, 0.03, 0.04]\n",
      "---------------user 82------------\n",
      " \n",
      "Top 5 ranked queries:  ['67', '116', '471', '476', '748']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 97.81, 97.1, 96.97]\n",
      "Most similar queries to each of the top ranked:  [583, 1051, 812, 1500, 204]\n",
      "Occurences of the most similar:  [0.36, 0.33, 0.24, 0.36, 0.27]\n",
      "similarity of most similar wrt original query:  [0.04, 0.04, 0.06, 0.04, 0.07]\n",
      "Overall similarity:  [0.03, 0.02, 0.04, 0.01, 0.04]\n",
      "---------------user 83------------\n",
      " \n",
      "Top 5 ranked queries:  ['315', '321', '400', '544', '621']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.87, 94.56, 92.64]\n",
      "Most similar queries to each of the top ranked:  [402, 422, 1444, 873, 769]\n",
      "Occurences of the most similar:  [0.34, 0.31, 0.26, 0.35, 0.31]\n",
      "similarity of most similar wrt original query:  [0.07, 0.05, 0.14, 0.07, 0.07]\n",
      "Overall similarity:  [0.05, 0.03, 0.04, 0.03, 0.02]\n",
      "---------------user 84------------\n",
      " \n",
      "Top 5 ranked queries:  ['326', '389', '660', '673', '858']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 97.84, 97.78, 97.69]\n",
      "Most similar queries to each of the top ranked:  [1362, 1958, 1588, 933, 5]\n",
      "Occurences of the most similar:  [0.21, 0.3, 0.41, 0.39, 0.35]\n",
      "similarity of most similar wrt original query:  [0.07, 0.06, 0.05, 0.05, 0.03]\n",
      "Overall similarity:  [0.04, 0.03, 0.04, 0.03, 0.02]\n",
      "---------------user 85------------\n",
      " \n",
      "Top 5 ranked queries:  ['35', '310', '368', '443', '791']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 91.67]\n",
      "Most similar queries to each of the top ranked:  [812, 1545, 562, 568, 562]\n",
      "Occurences of the most similar:  [0.24, 0.25, 0.34, 0.27, 0.34]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.06, 0.06, 0.06]\n",
      "Overall similarity:  [0.01, 0.01, 0.03, 0.01, 0.04]\n",
      "---------------user 86------------\n",
      " \n",
      "Top 5 ranked queries:  ['4', '52', '70', '121', '128']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.59, 96.51, 96.41]\n",
      "Most similar queries to each of the top ranked:  [1545, 1588, 1362, 1701, 1545]\n",
      "Occurences of the most similar:  [0.25, 0.41, 0.21, 0.31, 0.25]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.07, 0.1, 0.06]\n",
      "Overall similarity:  [0.01, 0.04, 0.05, 0.05, 0.01]\n",
      "---------------user 87------------\n",
      " \n",
      "Top 5 ranked queries:  ['256', '509', '642', '736', '1036']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 91.67]\n",
      "Most similar queries to each of the top ranked:  [638, 120, 204, 1362, 422]\n",
      "Occurences of the most similar:  [0.24, 0.32, 0.27, 0.21, 0.31]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.07, 0.07, 0.05]\n",
      "Overall similarity:  [0.03, 0.03, 0.01, 0.04, 0.03]\n",
      "---------------user 88------------\n",
      " \n",
      "Top 5 ranked queries:  ['9', '13', '74', '88', '93']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 95.36, 94.87, 94.15]\n",
      "Most similar queries to each of the top ranked:  [764, 1230, 1362, 562, 108]\n",
      "Occurences of the most similar:  [0.33, 0.31, 0.21, 0.34, 0.26]\n",
      "similarity of most similar wrt original query:  [0.5, 0.06, 0.07, 0.06, 0.07]\n",
      "Overall similarity:  [0.29, 0.03, 0.05, 0.04, 0.03]\n",
      "---------------user 89------------\n",
      " \n",
      "Top 5 ranked queries:  ['46', '151', '287', '652', '682']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 92.42]\n",
      "Most similar queries to each of the top ranked:  [1648, 1540, 1958, 387, 23]\n",
      "Occurences of the most similar:  [0.33, 0.32, 0.3, 0.29, 0.34]\n",
      "similarity of most similar wrt original query:  [0.04, 0.02, 0.06, 0.05, 0.8]\n",
      "Overall similarity:  [0.03, 0.01, 0.03, 0.02, 0.6]\n",
      "---------------user 90------------\n",
      " \n",
      "Top 5 ranked queries:  ['410', '457', '579', '986', '1308']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 91.67]\n",
      "Most similar queries to each of the top ranked:  [1701, 1435, 1355, 583, 1958]\n",
      "Occurences of the most similar:  [0.31, 0.37, 0.27, 0.36, 0.3]\n",
      "similarity of most similar wrt original query:  [0.1, 0.09, 0.04, 0.04, 0.06]\n",
      "Overall similarity:  [0.04, 0.04, 0.03, 0.03, 0.03]\n",
      "---------------user 91------------\n",
      " \n",
      "Top 5 ranked queries:  ['37', '142', '212', '421', '466']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 91.67]\n",
      "Most similar queries to each of the top ranked:  [1362, 638, 1506, 587, 1931]\n",
      "Occurences of the most similar:  [0.21, 0.24, 0.24, 0.29, 0.34]\n",
      "similarity of most similar wrt original query:  [0.07, 0.06, 0.09, 0.05, 0.06]\n",
      "Overall similarity:  [0.04, 0.01, 0.04, 0.04, 0.01]\n",
      "---------------user 92------------\n",
      " \n",
      "Top 5 ranked queries:  ['167', '211', '1127', '1324', '1332']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 95.43, 94.96]\n",
      "Most similar queries to each of the top ranked:  [1931, 1096, 1545, 1669, 1962]\n",
      "Occurences of the most similar:  [0.34, 0.31, 0.25, 0.34, 0.36]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.06, 0.06, 0.05]\n",
      "Overall similarity:  [0.01, 0.02, 0.01, 0.04, 0.02]\n",
      "---------------user 93------------\n",
      " \n",
      "Top 5 ranked queries:  ['70', '110', '348', '432', '576']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 95.83, 93.75, 91.67]\n",
      "Most similar queries to each of the top ranked:  [1362, 431, 1230, 120, 1355]\n",
      "Occurences of the most similar:  [0.21, 0.28, 0.31, 0.32, 0.27]\n",
      "similarity of most similar wrt original query:  [0.07, 0.8, 0.06, 0.06, 0.04]\n",
      "Overall similarity:  [0.05, 0.65, 0.01, 0.03, 0.02]\n",
      "---------------user 94------------\n",
      " \n",
      "Top 5 ranked queries:  ['727', '787', '793', '822', '853']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 95.92, 93.88, 93.71]\n",
      "Most similar queries to each of the top ranked:  [764, 402, 568, 583, 1048]\n",
      "Occurences of the most similar:  [0.33, 0.34, 0.27, 0.36, 0.46]\n",
      "similarity of most similar wrt original query:  [0.5, 0.07, 0.06, 0.04, 0.07]\n",
      "Overall similarity:  [0.18, 0.04, 0.01, 0.03, 0.05]\n",
      "---------------user 95------------\n",
      " \n",
      "Top 5 ranked queries:  ['32', '111', '225', '357', '417']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.55, 98.23, 97.1, 97.0]\n",
      "Most similar queries to each of the top ranked:  [1230, 954, 1048, 1069, 1069]\n",
      "Occurences of the most similar:  [0.31, 0.38, 0.46, 0.33, 0.33]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.07, 0.05, 0.05]\n",
      "Overall similarity:  [0.02, 0.02, 0.04, 0.03, 0.03]\n",
      "---------------user 96------------\n",
      " \n",
      "Top 5 ranked queries:  ['247', '328', '385', '407', '710']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 94.9, 94.87, 94.13]\n",
      "Most similar queries to each of the top ranked:  [1738, 1125, 1362, 1128, 638]\n",
      "Occurences of the most similar:  [0.3, 0.27, 0.21, 0.23, 0.24]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.07, 0.86, 0.06]\n",
      "Overall similarity:  [0.02, 0.02, 0.04, 0.56, 0.01]\n",
      "---------------user 97------------\n",
      " \n",
      "Top 5 ranked queries:  ['313', '409', '1686', '414', '1042']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 98.98, 97.96, 96.94, 95.92]\n",
      "Most similar queries to each of the top ranked:  [812, 1811, 709, 608, 48]\n",
      "Occurences of the most similar:  [0.24, 0.35, 0.4, 0.31, 0.39]\n",
      "similarity of most similar wrt original query:  [0.06, 0.06, 0.04, 0.71, 0.07]\n",
      "Overall similarity:  [0.03, 0.01, 0.02, 0.5, 0.07]\n",
      "---------------user 98------------\n",
      " \n",
      "Top 5 ranked queries:  ['37', '91', '127', '198', '670']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.44, 96.9, 96.82, 96.69]\n",
      "Most similar queries to each of the top ranked:  [1362, 434, 402, 608, 1457]\n",
      "Occurences of the most similar:  [0.21, 0.2, 0.34, 0.31, 0.31]\n",
      "similarity of most similar wrt original query:  [0.07, 0.8, 0.07, 0.71, 0.05]\n",
      "Overall similarity:  [0.04, 0.53, 0.03, 0.44, 0.03]\n",
      "---------------user 99------------\n",
      " \n",
      "Top 5 ranked queries:  ['163', '193', '260', '298', '309']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.92, 97.67, 97.52, 97.48]\n",
      "Most similar queries to each of the top ranked:  [943, 48, 1986, 1545, 709]\n",
      "Occurences of the most similar:  [0.28, 0.39, 0.34, 0.25, 0.4]\n",
      "similarity of most similar wrt original query:  [0.07, 0.07, 0.07, 0.06, 0.04]\n",
      "Overall similarity:  [0.04, 0.07, 0.02, 0.01, 0.02]\n",
      "---------------user 100------------\n",
      " \n",
      "Top 5 ranked queries:  ['298', '435', '507', '629', '636']\n",
      "Rank of top 5 ranked queries (normalized):  [100.0, 97.96, 96.57, 96.41, 95.94]\n",
      "Most similar queries to each of the top ranked:  [1545, 1457, 683, 1345, 1635]\n",
      "Occurences of the most similar:  [0.25, 0.31, 0.29, 0.27, 0.33]\n",
      "similarity of most similar wrt original query:  [0.06, 0.05, 0.4, 0.05, 0.06]\n",
      "Overall similarity:  [0.01, 0.02, 0.18, 0.03, 0.02]\n"
     ]
    }
   ],
   "source": [
    "if case == 1:\n",
    "    importance = pd.DataFrame(0, index = range(len(user_queries)), columns =['user_id','importance_value'])\n",
    "    dict_query = {}\n",
    "    # We create a dictionary with the possible combinations:\n",
    "    comb, l = auxiliary_functions.combination(query_columns)\n",
    "    for i in range(l):\n",
    "        dict_query.update({str(comb[i]) : []} )\n",
    "    length = len(query_columns)\n",
    "    dict_query = auxiliary_functions.matching_queries(length, query_columns, query, dict_query, queries)\n",
    "    \n",
    "    # For the queries in the dictionary we create the query set to calculate similaritis later\n",
    "    all_values = dict_query.values()\n",
    "    index_values_dict = list(chain.from_iterable(list(all_values)))\n",
    "    sim_queries = queries.iloc[index_values_dict]\n",
    "    \n",
    "    # We can calculate the similarity between the original query and the ones that share some conditions\n",
    "    random_query_set = list(auxiliary_functions.queries_as_sets(random_query, filename='random_query.json').values())[0]\n",
    "    print(random_query_set)\n",
    "    similarity_value_query = pd.DataFrame(0, index = range(len(sim_queries)), columns = ['query_id', 'sim_value'])\n",
    "    similarity_value_query['query_id'] = sim_queries['query_id'].tolist()\n",
    "    similarity = []\n",
    "\n",
    "    for query_id in sim_queries['query_id']:\n",
    "        gvn_jsonfile = open(\"query_set.json\")\n",
    "        json_data = json.load(gvn_jsonfile)\n",
    "        set_query = json_data[str(query_id)]     \n",
    "        similarity.append(auxiliary_functions.jaccard_similarity(random_query_set, set_query))\n",
    "\n",
    "    similarity_value_query['sim_value'] = similarity\n",
    "    \n",
    "    imp = []\n",
    "    for i in range(len(user_queries)):\n",
    "        gvn_jsonfile = open(\"query_set.json\")\n",
    "        json_data = json.load(gvn_jsonfile)\n",
    "\n",
    "        print(\"---------------user {}------------\\n \".format(i+1))\n",
    "        dict_cluster_sim = {}\n",
    "        user_queries_non_nan = []\n",
    "        user_queries_non_nan_rank = []\n",
    "        user_queries_nan = []      \n",
    "        \n",
    "        user_queries_index = [str(j) for j in user_queries_fill_minmax.columns[1:]]\n",
    "        user_queries_rank = [round(j,2) for j in user_queries_fill_minmax.iloc[i,1:]]\n",
    "        top_5_index_queries = auxiliary_functions.sort_by_indexes(user_queries_index, user_queries_rank, True)[:5]\n",
    "        top_5_rank_queries = auxiliary_functions.find_highest_values(user_queries_rank, ordered_nums_to_return=5)\n",
    "        print('Top 5 ranked queries: ', top_5_index_queries)\n",
    "        print('Rank of top 5 ranked queries (normalized): ',top_5_rank_queries )\n",
    "        \n",
    "        # We look at the 5 highest ranked queries\n",
    "        #top_5_index_queries = auxiliary_functions.sort_by_indexes(user_queries_non_nan, user_queries_non_nan_rank, True)[:5]\n",
    "        #top_5_rank_queries = auxiliary_functions.find_highest_values(user_queries_non_nan_rank, ordered_nums_to_return=5)\n",
    "        #print('Top 5 ranked queries: ', top_5_index_queries)\n",
    "        #print('Rank of top 5 ranked queries (normalized): ',top_5_rank_queries )\n",
    "                \n",
    "        #print('Visited queries: ', len(user_queries_non_nan))\n",
    "        #print('Not visited queries: ', len(user_queries_nan))\n",
    "\n",
    "        # Create a dictionary\n",
    "        for j in range(len(np.unique(queries['kmeans_label_id']))):\n",
    "            dict_cluster_sim.update({str(np.unique(queries['kmeans_label_id'])[j]) : []})\n",
    "        \n",
    "        for k in range(len(sim_queries)):\n",
    "            dict_cluster_sim[str(queries['kmeans_label_id'].iloc[k])].append(sim_queries['query_id'].iloc[k])\n",
    "\n",
    "        index_top_sim = [0,0,0,0,0]\n",
    "        value_top_sim = [0,0,0,0,0]\n",
    "        sim_item_original = []\n",
    "        occurrences = []\n",
    "        for t, item in enumerate(top_5_index_queries):\n",
    "            set_query_non_nan = json_data[str(item)]\n",
    "            key = str(queries['kmeans_label_id'].iloc[int(item)]) \n",
    "            # We calculate  the similarity between the top ranked and the original query\n",
    "            sim_item_original.append(round(auxiliary_functions.jaccard_similarity(set_query_non_nan, random_query_set),2))\n",
    "            \n",
    "            sim_value = 0\n",
    "            most_similar_index = 0\n",
    "            for query_id in dict_cluster_sim[key]:\n",
    "                gvn_jsonfile = open(\"query_set.json\")\n",
    "                json_data = json.load(gvn_jsonfile)\n",
    "                set_query = json_data[str(query_id)]\n",
    "                similarity_value = auxiliary_functions.jaccard_similarity(set_query_non_nan, set_query)\n",
    "                \n",
    "                if similarity_value > sim_value:\n",
    "                    sim_value = round(similarity_value,2)\n",
    "                    value_top_sim[t] = sim_value\n",
    "                    index_top_sim[t] = query_id\n",
    "                    most_similar_index = query_id\n",
    "            \n",
    "            occurrences.append((len(user_queries) - user_queries[str(most_similar_index)].isnull().sum())/len(user_queries))\n",
    "\n",
    "    \n",
    "        print('Most similar queries to each of the top ranked: ', index_top_sim)\n",
    "        print('Occurences of the most similar: ', occurrences)\n",
    "        #print('Similarity of most similar queries to each of the top ranked: ', value_top_sim)\n",
    "        #print('Similarity of top ranked by user and original query: ', sim_item_original)\n",
    "        \n",
    "        similarity_query_random = []\n",
    "        for l in range(len(index_top_sim)):\n",
    "            similarity_query_random.append(round(similarity_value_query['sim_value'][similarity_value_query['query_id'] ==index_top_sim[l]].tolist()[0],2))\n",
    "            \n",
    "        print('similarity of most similar wrt original query: ', similarity_query_random)\n",
    "        \n",
    "        weights = [round(i*j,2) for i,j in zip(similarity_query_random, value_top_sim)]\n",
    "        print('Overall similarity: ', weights)\n",
    "        \n",
    "        importance_user = mean([i*j*k/100 for i,j,k in zip(top_5_rank_queries, weights,occurrences)])\n",
    "        imp.append(importance_user)\n",
    "        #print('imortance of the query: ', importance_user)\n",
    "    \n",
    "    importance['user_id'] = list(user_queries['user_id'])\n",
    "    importance['importance_value'] = imp\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id             899-29-8267\n",
       "importance_value       0.089133\n",
       "dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "importance.max()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can base the importance or relevance of a query in different aspects:\n",
    "<ul>\n",
    "    <li>  The ranking of queries with similar value of Jaccard similarity</li>\n",
    "    <li> The ranking of queries that share some of the condition and their values </li>\n",
    "    <li> The number of queries that were already posed by the user and have similar conditions </li> \n",
    "</ul>"
   ]
  }
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