Microblog Entity Linking with Social Temporal Context

Wen Hua, Kai Zheng, Xiaofang Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

34 Citations (Scopus)

Abstract

Nowadays microblogging sites, such as Twitter and Chinese Sina Weibo, have established themselves as an invaluable information source, which provides a huge collection of manually-generated tweets with broad range of topics from daily life to breaking news. Entity linking is indispensable for understanding and maintaining such information, which in turn facilitates many real-world applications such as tweet clustering and classification, personalized microblog search, and so forth. However, tweets are short, informal and error-prone, rendering traditional approaches for entity linking in documents largely inapplicable. Recent work addresses this problem by utilising information from other tweets and linking entities in a batch manner. Nevertheless, the high computational complexity makes this approach infeasible for real-time applications given the high arrival rate of tweets. In this paper, we propose an efficient solution to link entities in tweets by analyzing their social and temporal context. Our proposed framework takes into consideration three features, namely entity popularity, entity recency, and user interest information embedded in social interactions to assist the entity linking task. E.ective indexing structures along with incremental algorithms have also been developed to reduce the computation and maintenance costs of our approach. Experimental results based on real tweet datasets verify the e.ectiveness and efficiency of our proposals.

Original languageEnglish
Title of host publicationSIGMOD 2015 - Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages1761-1775
Number of pages15
ISBN (Electronic)9781450327589
DOIs
Publication statusPublished - 27 May 2015
Externally publishedYes
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2015 - Melbourne, Australia
Duration: 31 May 20154 Jun 2015

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
Volume2015-May
ISSN (Print)0730-8078

Conference

ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2015
Country/TerritoryAustralia
CityMelbourne
Period31/05/154/06/15

Keywords

  • Entity popularity
  • Entity recency
  • Microblog entity linking
  • Social temporal context
  • User interest

ASJC Scopus subject areas

  • Information Systems

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