Entity-Based Relevance Feedback for Document Retrieval

Eilon Sheetrit, Fiana Raiber, Oren Kurland

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

Abstract

There is a long history of work on using relevance feedback for ad hoc document retrieval. The main types of relevance feedback studied thus far are for documents, passages and terms. We explore the merits of using relevance feedback provided for entities in an entity repository. We devise retrieval methods that can utilize relevance feedback provided for tokens whether entities or terms. Empirical evaluation shows that using entity relevance feedback falls short with respect to utilizing term feedback on average, but is much more effective for difficult queries. Furthermore, integrating term and entity relevance feedback is of clear merit; e.g., for augmenting minimal document feedback. We also contrast approaches to presenting entities and terms for soliciting relevance feedback.

Original languageEnglish
Title of host publicationICTIR 2023 - Proceedings of the 2023 ACM SIGIR International Conference on the Theory of Information Retrieval
Pages177-187
Number of pages11
ISBN (Electronic)9798400700736
DOIs
StatePublished - 9 Aug 2023
Event9th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2023 - Taipei, Taiwan, Province of China
Duration: 23 Jul 2023 → …

Publication series

NameICTIR 2023 - Proceedings of the 2023 ACM SIGIR International Conference on the Theory of Information Retrieval

Conference

Conference9th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period23/07/23 → …

Keywords

  • document retrieval
  • entity relevance feedback
  • query expansion

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems

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