yao8839836/KGE-LDA
Knowledge Graph Embedding LDA. AAAI 2017
This project helps researchers and data scientists analyze large collections of text documents by identifying underlying themes or topics. It takes a collection of documents and a related knowledge graph as input, then outputs a set of topics where each topic is described by relevant words and entities from the knowledge graph. This is useful for anyone trying to make sense of large text corpora in fields like scientific research or content analysis.
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Use this if you need to discover meaningful topics within a large document set and want to incorporate external structured knowledge (like Wikipedia or WordNet) to enrich topic definitions.
Not ideal if you primarily work with general text analysis and do not have or require the use of a pre-existing knowledge graph to enhance topic modeling.
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40
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Language
Java
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Last pushed
Aug 27, 2018
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