User and Document Group Approach of Clustering in Tagging Systems

Rong Pan, Guandong Xu, Peter Dolog

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

498 Downloads (Pure)

Abstract

In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.
Original languageEnglish
Title of host publicationProceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond
PublisherUniversity of Kassel
Publication dateOct 2010
Pages315-321
Chapter6
Publication statusPublished - Oct 2010
EventLWA 2010 - Kassel, Germany
Duration: 4 Oct 20106 Oct 2010

Conference

ConferenceLWA 2010
CountryGermany
CityKassel
Period04/10/201006/10/2010

Fingerprint

Recommender systems
Experiments

Bibliographical note

@article{panuser,
title={{User and Document Group Approach of Clustering in Tagging Systems}},
author={Pan, R. and Xu, G. and Dolog, P.}
}

Keywords

  • User Profile
  • Document Profile
  • Spectral Clustering
  • Group Profile
  • Modularity Metric

Cite this

Pan, R., Xu, G., & Dolog, P. (2010). User and Document Group Approach of Clustering in Tagging Systems. In Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond (pp. 315-321). University of Kassel.
Pan, Rong ; Xu, Guandong ; Dolog, Peter. / User and Document Group Approach of Clustering in Tagging Systems. Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond. University of Kassel, 2010. pp. 315-321
@inproceedings{c59f9f547870494996e37096a9eb18ff,
title = "User and Document Group Approach of Clustering in Tagging Systems",
abstract = "In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.",
keywords = "User Profile, Document Profile, Spectral Clustering, Group Profile, Modularity Metric",
author = "Rong Pan and Guandong Xu and Peter Dolog",
note = "@article{panuser, title={{User and Document Group Approach of Clustering in Tagging Systems}}, author={Pan, R. and Xu, G. and Dolog, P.} }",
year = "2010",
month = "10",
language = "English",
pages = "315--321",
booktitle = "Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond",
publisher = "University of Kassel",

}

Pan, R, Xu, G & Dolog, P 2010, User and Document Group Approach of Clustering in Tagging Systems. in Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond. University of Kassel, pp. 315-321, LWA 2010, Kassel, Germany, 04/10/2010.

User and Document Group Approach of Clustering in Tagging Systems. / Pan, Rong; Xu, Guandong; Dolog, Peter.

Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond. University of Kassel, 2010. p. 315-321.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - User and Document Group Approach of Clustering in Tagging Systems

AU - Pan, Rong

AU - Xu, Guandong

AU - Dolog, Peter

N1 - @article{panuser, title={{User and Document Group Approach of Clustering in Tagging Systems}}, author={Pan, R. and Xu, G. and Dolog, P.} }

PY - 2010/10

Y1 - 2010/10

N2 - In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.

AB - In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.

KW - User Profile

KW - Document Profile

KW - Spectral Clustering

KW - Group Profile

KW - Modularity Metric

M3 - Article in proceeding

SP - 315

EP - 321

BT - Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond

PB - University of Kassel

ER -

Pan R, Xu G, Dolog P. User and Document Group Approach of Clustering in Tagging Systems. In Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond. University of Kassel. 2010. p. 315-321