Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Web Search Relevance Feedback

  • Hui Fang
  • Cheng Xiang Zhai
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_462

Definition

Relevance feedback refers to an interactive cycle that helps to improve the retrieval performance based on the relevance judgments provided by a user. Specifically, when a user issues a query to describe an information need, an information retrieval system would first return a set of initial results and then ask the user to judge whether some information items (typically documents or passages) are relevant or not. After that, the system would reformulate the query based on the collected feedback information, and return a set of retrieval results, which presumably would be better than the initial retrieval results. This procedure could be repeated.

Historical Background

Quality of retrieval results highly depends on how effective a user’s query (usually a set of keywords) is in distinguishing relevant documents from non-relevant ones. Ideally, the keywords used in the query should occur only in the relevant documents and not in any non-relevant document. Unfortunately, in...

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of DelawareNewarkUSA
  2. 2.University of Illinois at Urbana-ChampaignUrbanaUSA

Section editors and affiliations

  • Cong Yu
    • 1
  1. 1.Google ResearchNew YorkUSA