A document query search using an extended centrality with the Word2vec

Wooju Kim, Heewon Jang, Hak Jin Kim, Donghe Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution


While everyday document search is done by keyword-based queries to search engines, we have situations that need deep search of documents such as scrutinies of patents, legal documents, and so on. In such cases, using document queries, instead of keyword-based queries, can be more helpful because it exploits more information from the query document. 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.

Original languageEnglish
Title of host publicationProceedings of the 18th Annual International Conference on Electronic Commerce
Subtitle of host publicatione-Commerce in Smart connected World, ICEC 2016
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450342223
Publication statusPublished - 2016 Aug 17
Event18th International Conference on Electronic Commerce, ICEC 2016 - Suwon, Korea, Republic of
Duration: 2016 Aug 172016 Aug 19

Publication series

NameACM International Conference Proceeding Series


Other18th International Conference on Electronic Commerce, ICEC 2016
Country/TerritoryKorea, Republic of

Bibliographical note

Publisher Copyright:
Copyright is held by the owner/author(s).

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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