Ranking Very Many Typed Entities on Wikipedia

Hugo Zaragoza, H. Rode, Peter Mika, Jordi Atserias, Massimiliano Ciaramita, Guiseppe Attardi

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

55 Citations (Scopus)

Abstract

We discuss the problem of ranking very many entities of different types. In particular we deal with a heterogeneous set of types, some being very generic and some very specific. We discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a Web search engine to compute entity relevance. We evaluate these approaches on the real task of ranking Wikipedia entities typed with a state-of-the-art named-entity tagger. Results show that both approaches can greatly increase the performance of methods based only on passage retrieval.
Original languageUndefined
Title of host publicationProceedings of the sixteenth ACM conference on Conference on information and knowledge management, CIKM '07
Place of PublicationNew York, NY, USA
PublisherACM Press
Pages1015-1018
Number of pages4
ISBN (Print)978-1-59593-803-9
DOIs
Publication statusPublished - Nov 2007
Event16th ACM conference on Conference on Information and Knowledge Management, CIKM 2007 - Lisbon, Portugal
Duration: 6 Nov 20079 Nov 2007
Conference number: 16

Publication series

Name
PublisherACM Press
NumberFS-07-05

Conference

Conference16th ACM conference on Conference on Information and Knowledge Management, CIKM 2007
Abbreviated titleCIKM
CountryPortugal
CityLisbon
Period6/11/079/11/07

Keywords

  • EWI-11439
  • CR-H.3.3
  • METIS-245789
  • IR-62024
  • DB-XMLIR: XML INFORMATION RETRIEVAL

Cite this