Specializing Word Embeddings for Similarity or Relatedness
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Document ClassificationNamed Entity Recognition (NER)Sentiment AnalysisWord EmbeddingsSimilar Papers 제목 키워드 기반
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Word embeddings learned from text corpus can be improved by injecting knowledge from external resources, while at the same time also specializing them for similarity or relatedness. These knowledge resources (like WordNe…
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Word embeddings obtained from neural network models such as Word2Vec Skipgram have become popular representations of word meaning and have been evaluated on a variety of word similarity and relatedness norming data. Skip…
Word EmbeddingsWord SimilarityEnhanced Word Representations for Bridging Anaphora Resolution
Most current models of word representations(e.g.,GloVe) have successfully captured fine-grained semantics. However, semantic similarity exhibited in these word embeddings is not suitable for resolving bridging anaphora, …
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