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RESLVE: Leveraging User Interest to Improve Entity Disambiguation on Short Text

Abstract

We address the Named Entity Disambiguation (NED) prob- lem for short, user-generated texts on the social Web. In such settings, the lack of linguistic features and sparse lex- ical context result in a high degree of ambiguity and sharp performance drops of nearly 50% in the accuracy of conven- tional NED systems. We handle these challenges by develop- ing a model of user-interest with respect to a personal knowl- edge context; and Wikipedia, a particularly well-established and reliable knowledge base, is used to instantiate the proce- dure. We conduct systematic evaluations using individuals? posts from Twitter, YouTube, and Flickr and demonstrate that our novel technique is able to achieve substantial per- formance gains beyond state-of-the-art NED methods.

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Authors
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Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
Web of Linked Entities (WoLE)
Divisions
Multimedia Information Systems
Subjects
Webmanagement
Event Location
Rio de Janeiro
Event Type
Workshop
Event Dates
May 13th
Series Name
Web of Linked Entities (WoLE) Workshop, co-located with WWW2013
Date
13 May 2013
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