Encyclopedia of Database Systems

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

Relevance Feedback for Text Retrieval

  • Olga VechtomovaEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_949




Relevance feedback (RF) is a process by which the system, having retrieved some documents in response to the user’s query, asks the user to assess their relevance to his/her information need. The user’s relevance judgments are then used to either adjust the weights of the query terms, or add new terms to the query (query expansion).

Key Points

Searchers may have difficulties in finding the words and phrases (terms) to express their information needs accurately and completely. They may also use different words in the queries than the words used by the authors of documents. On the other hand, searchers tend to know relevant information when they see it. In other words, it may be easier for them to tell which documents are relevant, instead of formulating a detailed query.

A typical relevance feedback process consists of the following steps: the user formulates and submits an initial query to an information retrieval system, which retrieves a ranked list of...

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Recommended Reading

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    Carpineto C, de Mori R, Romano G, Bigi B. An information-theoretic approach to automatic query expansion. ACM Trans Inf Syst. 2001;19(1):1–27.CrossRefGoogle Scholar
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    Ruthven I, Lalmas M. A survey on the use of relevance feedback for information access systems. Knowl Eng Rev. 2003;18(2):95–145.CrossRefGoogle Scholar
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    Spärck JK, Walker S, Robertson SE. A probabilistic model of information retrieval: development and comparative experiments. Inf Process Manag. 2000;36(6):779–808. (Part 1); 809–840 (Part 2).CrossRefGoogle Scholar
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    Spink A, Jansen BJ, Ozmultu HC. Use of query reformulation and relevance feedback by Excite users. Internet Res Electron Netw Appl Policy. 2000;10(4):317–28.CrossRefGoogle Scholar
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    White RW, Ruthven I, Jose JM. A study of factors affecting the utility of implicit relevance feedback. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2005. p. 35–42.Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.University of WaterlooWaterlooCanada

Section editors and affiliations

  • Edie Rasmussen
    • 1
  1. 1.Library, Archival & Inf. StudiesThe Univ. of British ColumbiaVancouverCanada