An evaluation of evolved term-weighting schemes in information retrieval

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

5 Citations (Scopus)

Abstract

This paper presents an evaluation of evolved term-weighting schemes on short, medium and long TREC queries. A previously evolved global (collection-wide) term-weighting scheme is evaluated on unseen TREC data and is shown to increase mean average precision over idf. A local (within-document) evolved term-weighting scheme is presented which is dependent on the best performing global scheme. The full evolved scheme (i.e. the combined local and global scheme) is compared to both the BM25 scheme and the Pivoted Normalisation scheme. Our results show that the local evolved solution does not perform well on some collections due to its document normalisation properties and we conclude that Okapi-tf can be tuned to interact effectively with the evolved global weighting scheme presented and increase mean average precision over the standard BM25 scheme.

Original languageEnglish
Title of host publicationCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Pages305-306
Number of pages2
DOIs
Publication statusPublished - 2005
EventCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany
Duration: 31 Oct 20055 Nov 2005

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

ConferenceCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Country/TerritoryGermany
CityBremen
Period31/10/055/11/05

Keywords

  • Genetic Programming
  • Information Retrieval
  • Term-Weighting

Fingerprint

Dive into the research topics of 'An evaluation of evolved term-weighting schemes in information retrieval'. Together they form a unique fingerprint.

Cite this