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Automatic keyphrase extraction and ontology mining for content‐based tag recommendation
Author(s) -
Pudota Nirmala,
Dattolo Antonina,
Baruzzo Andrea,
Ferrara Felice,
Tasso Carlo
Publication year - 2010
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20448
Subject(s) - computer science , ontology , information retrieval , domain (mathematical analysis) , testbed , set (abstract data type) , annotation , world wide web , information extraction , web content , web page , artificial intelligence , mathematical analysis , philosophy , mathematics , epistemology , programming language
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.