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Wang, Jiaan (Jervis)
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--- owner: hid: 233 name: Wang, Jiaan firstname: Jiaan lastname: Wang longitude: -86.494256 latitude: 39.173413 city: Bloomington, IN, U.S.A. url: https://github.com/bigdata-i523/hid233 paper1: abstract: > The growth of big data and its various applications in the media and entertainment industry has been swift in recent years as well as the rapid surge of big data and the increasing need for big data technologies. We describe the problems that come with big data and its challenges in the industry. We then present various utilization of big data and why big data is important to the advancement of the media and entertainment industry. author: - Wang, Jiaan chapter: Media hid: - 233 status: Nov 03 17 100% title: Big Data Applications in the Media and Entertainment Industry url: https://github.com/bigdata-i523/hid233/blob/master/paper1/report.tex paper2: abstract: > In the age of big data, artificial intelligence and speech recognition techniques have been widely used in numerous big data technologies and applications. Among those are virtual assistants which could potentially lead to the future evolution of big data. We list various virtual assistants currently in the industry developed by giants such as Google, Microsoft, Amazon and Apple. We then follow up by discussing some future development of virtual assistants. author: - Wang, Jiaan chapter: Technology hid: - 233 status: Nov 10 17 100% title: Big Data Applications in Virtual Assistants url: https://github.com/bigdata-i523/hid233/blob/master/paper2/report.tex project: abstract: > For years, people have been trying to reduce their automobile insurance bills. Insurance companies claim that price will be reduced for good drivers and raised for bad ones. However, inaccuracies in their data predictions lead to the exact opposite. The dataset being used is released by Porto Seguro, an auto and homeowner insurance company from Brazil. It consists of information from several hundred thousands of policyholders. The goal is to predict the probability an auto insurance policyholder files a claim the next year using classification algorithms. A good prediction with decent accuracy can correctly adjust prices for policyholders. author: - Wang, Jiaan - Chaturvedi, Dhawal chapter: Business hid: - 233 - 204 status: Dec 11 17 100% title: Big Data in Safe Driver Prediction type: project url: https://github.com/bigdata-i523/hid233/blob/master/project/
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