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http://dx.doi.org/10.5392/JKCA.2016.16.10.687

Semantic Extention Search for Documents Using the Word2vec  

Kim, Woo-ju (연세대학교 정보산업공학과)
Kim, Dong-he (한국철도기술연구원)
Jang, Hee-won (연세대학교 정보산업공학과)
Publication Information
The Journal of the Korea Contents Association / v.16, no.10, 2016 , pp. 687-692 More about this Journal
Abstract
Conventional way to search documents is keyword-based queries using vector space model, like tf-idf. Searching process of documents which is based on keywords can make some problems. it cannot recogize the difference of lexically different but semantically same words. This paper studies a scheme of document search based on document queries. In particular, it uses centrality vectors, instead of tf-idf vectors, to represent query documents, combined with the Word2vec method to capture the semantic similarity in contained words. This scheme improves the performance of document search and provides a way to find documents not only lexically, but semantically close to a query document.
Keywords
Semantic Search; Document Feature Vector; Vector Space Model; Word2vec;
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