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Using deep learning to create word embedding of named entities in a text

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Named Entity Embedding

This is a sample project on learning word embeddings of Named Entities from textual content. The assumption here is that the input corpus is composed of a sequence of named entities (e.g., using their labels from the DBpedia ontology) rather than raw text.

The implementation is based on the DL4J library. ⚠️ This project is still under active development.

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Using deep learning to create word embedding of named entities in a text

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