Identifying synonymy between relational phrases using word embeddings

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Identifying synonymy between relational phrases using word embeddings

Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Most of the previous work that has addressed this task of synonymy resolution uses similarity metrics between relational phrases based on textual stri...

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Two types of similarities between words have been studied in the natural language processing community: synonymy and relational similarity. A high degree of similarity exist between synonymous words. On the other hand, a high degree of relational similarity exists between analogous word pairs. We present and empirically test a hypothesis that links these two types of similarities. Specifically,...

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Relational phrases (e.g., “got married to”) and their hypernyms (e.g., “is a relative of”) are central for many tasks including question answering, open information extraction, paraphrasing, and entailment detection. This has motivated the development of several linguistic resources (e.g. DIRT, PATTY, and WiseNet) which systematically collect and organize relational phrases. These resources hav...

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Two words which share a sense are commonly called synonyms. They are equivalent in the context of that sense, and can be used interchangeably in a sentence which utilizes that sense. Two words are rarely synonyms for each other for all of their senses. With the advent of on-line-accessible lexicons it is possible to identify those words which are, in all contexts, interchangeable or `equivalent...

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ژورنال

عنوان ژورنال: Journal of Biomedical Informatics

سال: 2015

ISSN: 1532-0464

DOI: 10.1016/j.jbi.2015.05.010