Leveraging fine-grained wikipedia categories for entity search

Denghao Ma, Yueguo Chen, Kevin Chen Chuan Chang, Xiaoyong Du, Chuanfei Xu, Yi Chang

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

Abstract

Ad-hoc entity search, which is to retrieve a ranked list of relevant entities in response to a query of natural language question, has been widely studied. It has been shown that category matching of entities, especially when matching to fine-grained entity types/categories, is critical to the performance of entity search. However, the potentials of the fine-grained Wikipedia entity categories, has not been well exploited by existing studies. Based on the observation of how people describe entities of a specific type, we propose a headword-and-modifier model to deeply interpret both queries and fine-grained entity types/categories. Probabilistic generative models are designed to effectively estimate the relevance of headwords and modifiers as a pattern-based matching problem, taking the Wikipedia type taxonomy as an important input to address the ad-hoc representations of concepts/entities in queries. Extensive experimental results on three widely-used test sets: INEX-XER 2009, SemSearch-LS and TREC-Entity, show that our method achieves a significant improvement of the entity search performance over the state-of-the-art methods.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2018 - Proceedings of the World Wide Web Conference, WWW 2018
PublisherAssociation for Computing Machinery, Inc
Pages1623-1632
Number of pages10
ISBN (Electronic)9781450356398
DOIs
StatePublished - Apr 10 2018
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: Apr 23 2018Apr 27 2018

Publication series

NameThe Web Conference 2018 - Proceedings of the World Wide Web Conference, WWW 2018

Conference

Conference27th International World Wide Web, WWW 2018
CountryFrance
CityLyon
Period4/23/184/27/18

Keywords

  • Category matching
  • Entity search
  • Language model

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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  • Cite this

    Ma, D., Chen, Y., Chang, K. C. C., Du, X., Xu, C., & Chang, Y. (2018). Leveraging fine-grained wikipedia categories for entity search. In The Web Conference 2018 - Proceedings of the World Wide Web Conference, WWW 2018 (pp. 1623-1632). (The Web Conference 2018 - Proceedings of the World Wide Web Conference, WWW 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3178876.3186074