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Toward Recommendation Based on Ontology- Powered Web-Usage Mining.

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Title: Toward Recommendation Based on Ontology- Powered Web-Usage Mining.
Authors: Adda, Mehdi1 adda@ieee.org, Valtchev, Petko1 valtchev.petko@uqam.ca, Missaoui, Rokia2 rokia.missaoui@uqo.ca, Djeraba, Chabane3 Djeraba@lifl.fr
Source: IEEE Internet Computing. Jul/Aug2007, Vol. 11 Issue 4, p45-52. 8p. 1 Color Photograph, 2 Diagrams, 8 Charts, 1 Graph.
Subjects: Internet users, Relevance, Orthogonalization, Ontology, Algorithms, Data mining, Metadata, Decision support systems, Online data processing, Search engines
Abstract: Content adaptation on the Web reduces available information to a subset that matches a user's anticipated needs. Recommender systems rely on relevance scores for individual content items; in particular, pattern-based recommendation exploits co-occurrences of items in user sessions to ground any guesses about relevancy. To enhance the discovered patterns' quality, the authors propose using metadata about the content that they assume is stored in a domain ontology. Their approach comprises a dedicated pattern space built on top of the ontology, navigation primitives, mining methods, and recommendation techniques. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Internet Computing is the property of IEEE Computer Society 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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  Data: Toward Recommendation Based on Ontology- Powered Web-Usage Mining.
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  Data: <searchLink fieldCode="AR" term="%22Adda%2C+Mehdi%22">Adda, Mehdi</searchLink><relatesTo>1</relatesTo><i> adda@ieee.org</i><br /><searchLink fieldCode="AR" term="%22Valtchev%2C+Petko%22">Valtchev, Petko</searchLink><relatesTo>1</relatesTo><i> valtchev.petko@uqam.ca</i><br /><searchLink fieldCode="AR" term="%22Missaoui%2C+Rokia%22">Missaoui, Rokia</searchLink><relatesTo>2</relatesTo><i> rokia.missaoui@uqo.ca</i><br /><searchLink fieldCode="AR" term="%22Djeraba%2C+Chabane%22">Djeraba, Chabane</searchLink><relatesTo>3</relatesTo><i> Djeraba@lifl.fr</i>
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Internet+Computing%22">IEEE Internet Computing</searchLink>. Jul/Aug2007, Vol. 11 Issue 4, p45-52. 8p. 1 Color Photograph, 2 Diagrams, 8 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Internet+users%22">Internet users</searchLink><br /><searchLink fieldCode="DE" term="%22Relevance%22">Relevance</searchLink><br /><searchLink fieldCode="DE" term="%22Orthogonalization%22">Orthogonalization</searchLink><br /><searchLink fieldCode="DE" term="%22Ontology%22">Ontology</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Metadata%22">Metadata</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+support+systems%22">Decision support systems</searchLink><br /><searchLink fieldCode="DE" term="%22Online+data+processing%22">Online data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Search+engines%22">Search engines</searchLink>
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  Data: Content adaptation on the Web reduces available information to a subset that matches a user's anticipated needs. Recommender systems rely on relevance scores for individual content items; in particular, pattern-based recommendation exploits co-occurrences of items in user sessions to ground any guesses about relevancy. To enhance the discovered patterns' quality, the authors propose using metadata about the content that they assume is stored in a domain ontology. Their approach comprises a dedicated pattern space built on top of the ontology, navigation primitives, mining methods, and recommendation techniques. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Internet Computing is the property of IEEE Computer Society 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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        Text: English
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      – SubjectFull: Internet users
        Type: general
      – SubjectFull: Relevance
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      – SubjectFull: Orthogonalization
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      – SubjectFull: Ontology
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      – SubjectFull: Algorithms
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      – SubjectFull: Data mining
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      – SubjectFull: Metadata
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      – SubjectFull: Decision support systems
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      – SubjectFull: Online data processing
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      – SubjectFull: Search engines
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      – TitleFull: Toward Recommendation Based on Ontology- Powered Web-Usage Mining.
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              Text: Jul/Aug2007
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