Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 1041-1050, 2019.
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Abstract:
The \em word2vec methodology such as Skip-gram and CBOW has seen significant interest in recent years because of its ability to model semantic notions of word similarity and distances in sentences. A related methodology, referred to as \em doc2vec is also able to embed sentences and paragraphs. These methodologies, however, lead to differ...More
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