Learning personalized ontologies from text: A review on an inherently transdisciplinary area

Chen, S; Williams, MA

Learning personalized ontologies from text: A review on an inherently transdisciplinary area

Chen, S Williams, MA

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Publication Type:: Chapter
Citation:: Personalized Information Retrieval and Access: Concepts, Methods and Practices, 2008, pp. 1 - 29
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Chen, S	en_US
dc.contributor.author	Williams, MA https://orcid.org/0000-0002-1047-0503	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Personalized Information Retrieval and Access: Concepts, Methods and Practices, 2008, pp. 1 - 29	en_US
dc.identifier.isbn	9781599045108	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8014
dc.description.abstract	Ontology learning has been identified as an inherently transdisciplinary area. Personalized ontology learning for Web personalization involves Web technologies and therefore presents more challenges. This chapter presents a review of the main concepts of ontologies and the state of the art in the area of ontology learning from text. It provides an overview of Web personalization, and identifies issues and describes approaches for learning personalized ontologies. The goal of this survey is-through the study of the main concepts, existing methods, and practices of the area-to identify new connections with other areas for the future success of establishing principles for this new transdisciplinary area. As a result, the chapter is concluded by presenting a number of possible future research directions. © 2008, IGI Global.	en_US
dc.relation.ispartof	Personalized Information Retrieval and Access: Concepts, Methods and Practices	en_US
dc.relation.isbasedon	10.4018/978-1-59904-510-8.ch001	en_US
dc.title	Learning personalized ontologies from text: A review on an inherently transdisciplinary area	en_US
dc.type	Chapter
utslib.for	150302 Business Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Ontology learning has been identified as an inherently transdisciplinary area. Personalized ontology learning for Web personalization involves Web technologies and therefore presents more challenges. This chapter presents a review of the main concepts of ontologies and the state of the art in the area of ontology learning from text. It provides an overview of Web personalization, and identifies issues and describes approaches for learning personalized ontologies. The goal of this survey is-through the study of the main concepts, existing methods, and practices of the area-to identify new connections with other areas for the future success of establishing principles for this new transdisciplinary area. As a result, the chapter is concluded by presenting a number of possible future research directions. © 2008, IGI Global.

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http://hdl.handle.net/10453/8014