Cross-Domain Collaborative Filtering: A Brief Survey

Li, B

Cross-Domain Collaborative Filtering: A Brief Survey

Li, B

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: the 23rd IEEE International Conference on Tools with Artificial Intelligence, 2011, pp. 1085 - 1086
Issue Date:: 2011-01

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Field	Value	Language
dc.contributor.author	Li, B	en_US
dc.contributor.editor	Khoshgoftaar, TM	en_US
dc.contributor.editor	Zhu, XH	en_US
dc.date	2011-11-07	en_US
dc.date.issued	2011-01	en_US
dc.identifier.citation	the 23rd IEEE International Conference on Tools with Artificial Intelligence, 2011, pp. 1085 - 1086	en_US
dc.identifier.isbn	978-0-7695-4596-7	en_US
dc.identifier.uri	http://hdl.handle.net/10453/29565
dc.description.abstract	Cross-domain collaborative filtering (CF) is an emerging research topic in recommender systems. It aims to alleviate the sparsity problem in individual CF domains by transferring knowledge among related domains. In this paper, we will give a brief survey of the pilot studies in this research line in two dimensions: Collaborative Filtering Domains and Knowledge Transfer Styles. Some possible extensions for crossdomain CF will be discussed in the end.	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	the 23rd IEEE International Conference on Tools with Artificial Intelligence	en_US
dc.relation.ispartof	International Conference on Tools with Artificial Intelligence	en_US
dc.rights	© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	Cross-Domain Collaborative Filtering: A Brief Survey	en_US
dc.type	Conference Proceeding
utslib.location	Los Alamitos, California	en_US
utslib.location.activity	Boca Raton, Florida, USA	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Boca Raton, Florida, USA	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 Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Los Alamitos, California	en_US
pubs.start-date	2011-11-07	en_US

Abstract:

Cross-domain collaborative filtering (CF) is an emerging research topic in recommender systems. It aims to alleviate the sparsity problem in individual CF domains by transferring knowledge among related domains. In this paper, we will give a brief survey of the pilot studies in this research line in two dimensions: Collaborative Filtering Domains and Knowledge Transfer Styles. Some possible extensions for crossdomain CF will be discussed in the end.

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http://hdl.handle.net/10453/29565