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A task-focused literature recommender system for digital libraries.

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Title: A task-focused literature recommender system for digital libraries.
Authors: Yang, Wan-Shiou, Lin, Yi-Rong
Source: Online Information Review. 2013, Vol. 37 Issue 4, p581-601. 21p.
Subject Terms: *Library science research, Digital library research, Information services in science, Information services research, Algorithm research
Abstract: Purpose – The scientific literature has played an important role in the dissemination of new knowledge throughout the past century. However, the increasing numbers of scientific articles being published in recent years has intensified the perception of information overload for users attempting to find relevant scientific information. The purpose of this paper is to describe a task-focused strategy that employs the task profiles of users to make recommendations in a digital library. Design/method/approach – This paper combines information retrieval, common citation analysis, and coauthor relationship analysis techniques with a citation network analysis technique – the CiteRank algorithm – to find relevant and high-quality articles. In total, nine variations of the proposed approach were tested using articles downloaded from the CiteSeerX system and usage logs collected from the authors' experimental server. Findings – The results from the authors' experimental evaluations demonstrate that the proposed Content-citation approach outperforms the Relevance-CiteRank, Relevance-citation count, and Relevance-only approaches. Originality/value – This paper describes an original study that has produced a novel way to combine information retrieval, common citation analysis, and coauthor relationship analysis techniques to find relevant and high-quality articles for recommendation in a digital library. [ABSTRACT FROM AUTHOR]
Copyright of Online Information Review is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Availability: 0
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DbLabel: Education Research Complete
An: 90611680
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A task-focused literature recommender system for digital libraries.
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  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Yang%2C+Wan-Shiou%22">Yang, Wan-Shiou</searchLink><br /><searchLink fieldCode="AR" term="%22Lin%2C+Yi-Rong%22">Lin, Yi-Rong</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Online+Information+Review%22">Online Information Review</searchLink>. 2013, Vol. 37 Issue 4, p581-601. 21p.
– Name: Subject
  Label: Subject Terms
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  Data: *<searchLink fieldCode="DE" term="%22Library+science+research%22">Library science research</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+library+research%22">Digital library research</searchLink><br /><searchLink fieldCode="DE" term="%22Information+services+in+science%22">Information services in science</searchLink><br /><searchLink fieldCode="DE" term="%22Information+services+research%22">Information services research</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithm+research%22">Algorithm research</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose – The scientific literature has played an important role in the dissemination of new knowledge throughout the past century. However, the increasing numbers of scientific articles being published in recent years has intensified the perception of information overload for users attempting to find relevant scientific information. The purpose of this paper is to describe a task-focused strategy that employs the task profiles of users to make recommendations in a digital library. Design/method/approach – This paper combines information retrieval, common citation analysis, and coauthor relationship analysis techniques with a citation network analysis technique – the CiteRank algorithm – to find relevant and high-quality articles. In total, nine variations of the proposed approach were tested using articles downloaded from the CiteSeerX system and usage logs collected from the authors' experimental server. Findings – The results from the authors' experimental evaluations demonstrate that the proposed Content-citation approach outperforms the Relevance-CiteRank, Relevance-citation count, and Relevance-only approaches. Originality/value – This paper describes an original study that has produced a novel way to combine information retrieval, common citation analysis, and coauthor relationship analysis techniques to find relevant and high-quality articles for recommendation in a digital library. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Online Information Review is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=90611680
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      – Type: doi
        Value: 10.1108/OIR-10-2011-0172
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 581
    Subjects:
      – SubjectFull: Library science research
        Type: general
      – SubjectFull: Digital library research
        Type: general
      – SubjectFull: Information services in science
        Type: general
      – SubjectFull: Information services research
        Type: general
      – SubjectFull: Algorithm research
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      – TitleFull: A task-focused literature recommender system for digital libraries.
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              Text: 2013
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