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Discovery of Aggregate Usage Profiles based on Clustering Information Needs.

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Title: Discovery of Aggregate Usage Profiles based on Clustering Information Needs.
Authors: Azman, Azreen1 azreen@dcs.gla.ac.uk, Ounis, Iadh1 ounis@dcs.gla.ac.uk
Source: SIGIR Forum. 2004 Special Edition, p470-471. 2p. 2 Graphs.
Subjects: Information organization, Information retrieval, Computer programming, Algorithms, Documentation, Information resources management
Abstract: We present an alternative technique for discovering aggregate usage profiles from Web access logs. The technique is based on clustering information needs inferred from users' browsing paths. Browsing paths are extracted from users' access logs. Information need is inferred from each browsing path by using the Ostensive Model[1]. The technique is evaluated in a document recommendation application. We compare the performance of our technique against the well-established transaction-based technique proposed in [2]. Based on an initial evaluation, the results are encouraging. [ABSTRACT FROM AUTHOR]
Copyright of SIGIR Forum is the property of Association for Computing Machinery 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: Engineering Source
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DbLabel: Engineering Source
An: 15330496
AccessLevel: 6
PubType: Periodical
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  Data: Discovery of Aggregate Usage Profiles based on Clustering Information Needs.
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  Data: <searchLink fieldCode="AR" term="%22Azman%2C+Azreen%22">Azman, Azreen</searchLink><relatesTo>1</relatesTo><i> azreen@dcs.gla.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Ounis%2C+Iadh%22">Ounis, Iadh</searchLink><relatesTo>1</relatesTo><i> ounis@dcs.gla.ac.uk</i>
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  Data: <searchLink fieldCode="JN" term="%22SIGIR+Forum%22">SIGIR Forum</searchLink>. 2004 Special Edition, p470-471. 2p. 2 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Information+organization%22">Information organization</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Documentation%22">Documentation</searchLink><br /><searchLink fieldCode="DE" term="%22Information+resources+management%22">Information resources management</searchLink>
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  Data: We present an alternative technique for discovering aggregate usage profiles from Web access logs. The technique is based on clustering information needs inferred from users' browsing paths. Browsing paths are extracted from users' access logs. Information need is inferred from each browsing path by using the Ostensive Model[1]. The technique is evaluated in a document recommendation application. We compare the performance of our technique against the well-established transaction-based technique proposed in [2]. Based on an initial evaluation, the results are encouraging. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of SIGIR Forum is the property of Association for Computing Machinery 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.)
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      – Code: eng
        Text: English
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        PageCount: 2
        StartPage: 470
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      – SubjectFull: Information organization
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      – SubjectFull: Information retrieval
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      – SubjectFull: Computer programming
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      – SubjectFull: Algorithms
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      – SubjectFull: Documentation
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      – SubjectFull: Information resources management
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    Titles:
      – TitleFull: Discovery of Aggregate Usage Profiles based on Clustering Information Needs.
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            NameFull: Azman, Azreen
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            NameFull: Ounis, Iadh
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            – D: 25
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              Text: 2004 Special Edition
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              Y: 2004
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