Persistent Link:
http://hdl.handle.net/10150/105313
Title:
A Graph-based Recommender System for Digital Library
Author:
Huang, Zan; Chung, Wingyan; Ong, Thian-Huat; Chen, Hsinchun
Citation:
A Graph-based Recommender System for Digital Library 2002, :65-73
Publisher:
ACM/IEEE-CS
Issue Date:
2002
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105313
Submitted date:
2004-08-20
Abstract:
Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, useruser and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.
Type:
Conference Paper
Language:
en
Keywords:
Evaluation; Digital Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial Intelligence lab; AI lab; Recommender system; Hopfield net algorithm; Graph-based model; Content-based filtering; Collaborative; Filtering; Mutual information algorithm; Chinese phrase; Extraction

Full metadata record

DC FieldValue Language
dc.contributor.authorHuang, Zanen_US
dc.contributor.authorChung, Wingyanen_US
dc.contributor.authorOng, Thian-Huaten_US
dc.contributor.authorChen, Hsinchunen_US
dc.date.accessioned2004-08-20T00:00:01Z-
dc.date.available2010-06-18T23:23:29Z-
dc.date.issued2002en_US
dc.date.submitted2004-08-20en_US
dc.identifier.citationA Graph-based Recommender System for Digital Library 2002, :65-73en_US
dc.identifier.urihttp://hdl.handle.net/10150/105313-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractResearch shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, useruser and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherACM/IEEE-CSen_US
dc.subjectEvaluationen_US
dc.subjectDigital Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial Intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherRecommender systemen_US
dc.subject.otherHopfield net algorithmen_US
dc.subject.otherGraph-based modelen_US
dc.subject.otherContent-based filteringen_US
dc.subject.otherCollaborativeen_US
dc.subject.otherFilteringen_US
dc.subject.otherMutual information algorithmen_US
dc.subject.otherChinese phraseen_US
dc.subject.otherExtractionen_US
dc.titleA Graph-based Recommender System for Digital Libraryen_US
dc.typeConference Paperen_US
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