Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors

Rong Pan, Guandong Xu, Peter Dolog

Publikation: Bidrag til bog/antologi/rapport/konference proceedingBidrag til bog/antologiForskningpeer review

4 Citationer (Scopus)

Resumé

Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result demonstrates that our approach could considerably improve the performance of recommendations.
OriginalsprogEngelsk
TitelComputer Science and Convergence : CSA 2011 & WCC 2011 Proceedings
RedaktørerJames J. Park, Han-Chieh Chao, Mohammad S. Obaidat, Jongsung Kim
Antal sider10
ForlagSpringer
Publikationsdato2012
Sider355-364
ISBN (Trykt)978-94-007-2791-5
ISBN (Elektronisk)978-94-007-2792-2
DOI
StatusUdgivet - 2012
NavnLecture Notes in Electrical Engineering
Vol/bind114
ISSN1876-1100

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Collaborative filtering
Metadata
Clustering algorithms
Experiments

Citer dette

Pan, R., Xu, G., & Dolog, P. (2012). Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors. I J. J. Park, H-C. Chao, M. S. Obaidat, & J. Kim (red.), Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings (s. 355-364). Springer. Lecture Notes in Electrical Engineering, Bind. 114 https://doi.org/10.1007/978-94-007-2792-2_34
Pan, Rong ; Xu, Guandong ; Dolog, Peter. / Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors. Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings. red. / James J. Park ; Han-Chieh Chao ; Mohammad S. Obaidat ; Jongsung Kim. Springer, 2012. s. 355-364 (Lecture Notes in Electrical Engineering, Bind 114).
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abstract = "Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result demonstrates that our approach could considerably improve the performance of recommendations.",
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Pan, R, Xu, G & Dolog, P 2012, Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors. i JJ Park, H-C Chao, MS Obaidat & J Kim (red), Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings. Springer, Lecture Notes in Electrical Engineering, bind 114, s. 355-364. https://doi.org/10.1007/978-94-007-2792-2_34

Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors. / Pan, Rong; Xu, Guandong; Dolog, Peter.

Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings. red. / James J. Park; Han-Chieh Chao; Mohammad S. Obaidat; Jongsung Kim. Springer, 2012. s. 355-364 (Lecture Notes in Electrical Engineering, Bind 114).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingBidrag til bog/antologiForskningpeer review

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AB - Tag as a useful metadata reflects the collaborative and conceptual features of documents in social collaborative annotation systems. In this paper, we propose a collaborative approach for expanding tag neighbors and investigate the spectral clustering algorithm to filter out noisy tag neighbors in order to get appropriate recommendation for users. The preliminary experiments have been conducted on MovieLens dataset to compare our proposed approach with the traditional collaborative filtering recommendation approach and naive tag neighbors expansion approach in terms of precision, and the result demonstrates that our approach could considerably improve the performance of recommendations.

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Pan R, Xu G, Dolog P. Improving Recommendations in Tag-based Systems with Spectral Clustering of Tag Neighbors. I Park JJ, Chao H-C, Obaidat MS, Kim J, red., Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings. Springer. 2012. s. 355-364. (Lecture Notes in Electrical Engineering, Bind 114). https://doi.org/10.1007/978-94-007-2792-2_34