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Bibliographic Details
Main Authors: Cooper, Michael D., Chen, Hui-Min
Format: Recurso educativo Open Access
Language:en
Published: 2001
Subjects:
Online Access:https://eric.ed.gov/?id=EJ631338
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author Cooper, Michael D.
Chen, Hui-Min
author_facet Cooper, Michael D.
Chen, Hui-Min
Cooper, Michael D.
Chen, Hui-Min
collection Education Resources Information Center
contents Predicting the Relevance of a Library Catalog Search. Cooper, Michael D. Chen, Hui-Min Academic Libraries Higher Education Information Retrieval Information Seeking Library Catalogs Online Catalogs Online Searching Relevance (Information Retrieval) Search Strategies User Needs (Information) World Wide Web Proposes an operational definition of relevance for a Web-based library catalog. Proposes measures that characterize user behavior while searching a Web-based library catalog. Develops a methodology to predict when a user's search will be perceived to be relevant by the user. Tests the methodology with over 900,000 user search sessions with the University of California's Melvyl Web-based library catalog. (AEF)
format Recurso educativo Open Access
id eric_EJ631338
institution ERIC Institute of Education Sciences
language en
publishDate 2001
record_format eric
spellingShingle Predicting the Relevance of a Library Catalog Search.
Cooper, Michael D.
Chen, Hui-Min
Academic Libraries
Higher Education
Information Retrieval
Information Seeking
Library Catalogs
Online Catalogs
Online Searching
Relevance (Information Retrieval)
Search Strategies
User Needs (Information)
World Wide Web
Predicting the Relevance of a Library Catalog Search. Cooper, Michael D. Chen, Hui-Min Academic Libraries Higher Education Information Retrieval Information Seeking Library Catalogs Online Catalogs Online Searching Relevance (Information Retrieval) Search Strategies User Needs (Information) World Wide Web Proposes an operational definition of relevance for a Web-based library catalog. Proposes measures that characterize user behavior while searching a Web-based library catalog. Develops a methodology to predict when a user's search will be perceived to be relevant by the user. Tests the methodology with over 900,000 user search sessions with the University of California's Melvyl Web-based library catalog. (AEF)
title Predicting the Relevance of a Library Catalog Search.
topic Academic Libraries
Higher Education
Information Retrieval
Information Seeking
Library Catalogs
Online Catalogs
Online Searching
Relevance (Information Retrieval)
Search Strategies
User Needs (Information)
World Wide Web
url https://eric.ed.gov/?id=EJ631338