Mining for personal name aliases on the web

Danushka Bollegala, Taiki Honma, Yutaka Matsuo, Mitsuru Ishizuka

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

21 Citations (Scopus)

Abstract

We propose a novel approach to find aliases of a given name from the web. We exploit a set of known names and their aliases as training data and extract lexical patterns that convey information related to aliases of names from text snippets returned by a web search engine. The patterns are then used to find candidate aliases of a given name. We use anchor texts and hyperlinks to design a word co-occurrence model and define numerous ranking scores to evaluate the association between a name and its candidate aliases. The proposed method outperforms numerous baselines and previous work on alias extraction on a dataset of personal names, achieving a statistically significant mean reciprocal rank of 0.6718. Moreover, the aliases extracted using the proposed method improve recall by 20% in a relation-detection task.

Original languageEnglish
Title of host publicationProceeding of the 17th International Conference on World Wide Web 2008, WWW'08
Pages1107-1108
Number of pages2
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event17th International Conference on World Wide Web 2008, WWW'08 - Beijing
Duration: 2008 Apr 212008 Apr 25

Other

Other17th International Conference on World Wide Web 2008, WWW'08
CityBeijing
Period08/4/2108/4/25

Keywords

  • Name alias extraction
  • Semantic web
  • Web mining

ASJC Scopus subject areas

  • Computer Networks and Communications

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