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Automatic keyphrase extraction and ontology mining for content-based tag recommendation

2010; Wiley; Volume: 25; Issue: 12 Linguagem: Inglês

10.1002/int.20448

1098-111X

Nirmala Pudota, Antonina Dattolo, Andrea Baruzzo, Felice Ferrara, Carlo Tasso,

Advanced Text Analysis Techniques

International Journal of Intelligent SystemsVolume 25, Issue 12 p. 1158-1186 Research Article Automatic keyphrase extraction and ontology mining for content-based tag recommendation Nirmala Pudota, Nirmala Pudota [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorAntonina Dattolo, Corresponding Author Antonina Dattolo [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalyArtificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorAndrea Baruzzo, Andrea Baruzzo [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorFelice Ferrara, Felice Ferrara [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorCarlo Tasso, Carlo Tasso [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this author Nirmala Pudota, Nirmala Pudota [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorAntonina Dattolo, Corresponding Author Antonina Dattolo [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalyArtificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorAndrea Baruzzo, Andrea Baruzzo [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorFelice Ferrara, Felice Ferrara [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this authorCarlo Tasso, Carlo Tasso [email protected] Artificial Intelligence Laboratory, Department of Mathematics and Computer Science, University of Udine, 33100 Udine, ItalySearch for more papers by this author First published: 08 October 2010 https://doi.org/10.1002/int.20448Citations: 40Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Collaborative tagging represents for the Web a potential way for organizing and sharing information and for heightening the capabilities of existing search engines. However, because of the lack of automatic methodologies for generating the tags and supporting the tagging activity, many resources on the Web are deficient in tag information, and recommending opportune tags is both a current open issue and an exciting challenge. This paper approaches the problem by applying a combined set of techniques and tools (that uses tags, domain ontologies, keyphrase extraction methods) thereby generating tags automatically. The proposed approach is implemented in the PIRATES (Personalized Intelligent tag Recommender and Annotator TEStbed) framework, a prototype system for personalized content retrieval, annotation, and classification. A case study application is developed using a domain ontology for software engineering. © 2010 Wiley Periodicals, Inc. Citing Literature Volume25, Issue12Special Issue: New Trends for Ontology‐Based Knowledge DiscoveryDecember 2010Pages 1158-1186 RelatedInformation