On instant knowledge evolution from learning user search intent

Yen Kuan Lee, P.-H. Hsieh, Chi Hsuan Huang, Kun Ta Chuang

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

Abstract

In this paper, we explore a novel problem to identify timely new knowledge triples. In the literature, the need of knowledge enrichment has been recognized as the key to the success of semantic search. However, previous work of automatic knowledge extraction, such as Google Knowledge Vault, aim at identifying the unannotated knowledge triples from the full web-scale content in the offline execution. In our study, we show that most people demand the updated knowledge soon after the information is announced. However, the number of queries of such knowledge dramatically declines after a few days, meaning that the most people cannot obtain the precise knowledge from the execution of the offline knowledge enrichment when they inquire the answer of the timely events. To remedy this, we propose the SCKE framework to extract new knowledge triples which can be executed in the online scenario. We model the 'Query-Click' bipartite graph to extract the query correlation and to identify temporally coexistent entity pairs. Our experimental studies show that new triples can also be identified effectively and efficiently.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Web Services, ICWS 2016
EditorsStephan Reiff-Marganiec
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages562-569
Number of pages8
ISBN (Electronic)9781509026753
DOIs
Publication statusPublished - 2016 Aug 31
Event23rd IEEE International Conference on Web Services, ICWS 2016 - San Francisco, United States
Duration: 2016 Jun 272016 Jul 2

Publication series

NameProceedings - 2016 IEEE International Conference on Web Services, ICWS 2016

Other

Other23rd IEEE International Conference on Web Services, ICWS 2016
CountryUnited States
CitySan Francisco
Period16-06-2716-07-02

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

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  • Cite this

    Lee, Y. K., Hsieh, P-H., Huang, C. H., & Chuang, K. T. (2016). On instant knowledge evolution from learning user search intent. In S. Reiff-Marganiec (Ed.), Proceedings - 2016 IEEE International Conference on Web Services, ICWS 2016 (pp. 562-569). [7558048] (Proceedings - 2016 IEEE International Conference on Web Services, ICWS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICWS.2016.78