Top

Journal of Intelligent Information Systems

Published in:

01-04-2013

Folksonomy link prediction based on a tripartite graph for tag recommendation

Authors: Majdi Rawashdeh, Heung-Nam Kim, Jihad Mohamad Alja’am, Abdulmotaleb El Saddik

Published in: Journal of Intelligent Information Systems | Issue 2/2013

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Nowadays social tagging has become a popular way to annotate, search, navigate and discover online resources, in turn leading to the sheer amount of user-generated metadata. This paper addresses the problem of recommending suitable tags during folksonomy development from a graph-based perspective. The proposed approach adapts the Katz measure, a path-ensemble based proximity measure, for the use in social tagging systems. We model a folksonomy as a weighted, undirected tripartite graph. We then apply the Katz measure to this graph, and exploit it to provide tag recommendations for individual users. We evaluate our method on two real-world folksonomies collected from CiteULike and Last.fm. The experimental results demonstrate that the proposed method improves the recommendation performance and is effective for both active taggers and cold-start taggers compared to existing algorithms.

previous article Iterative classification for multiple target attributes

next article UniDis: a universal discretization technique

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

http://citeulike.org

http://www.last.fm/

http://www.citeulike.org/faq/data.adp

http://www.grouplens.org/node/462

Bischoff, K., Firan, C.S., Nejdl, W., Paiu, R. (2008). Can all tags be used for search? In Proceedings of the 17th ACM conference on information and knowledge management (pp. 193–202). New York: ACM.CrossRef

Box, G.E., Hunter, J.S., Hunter, W.G. (2005). Statistics for experimenters: Design, innovation, and discovery, 2nd ed. Wiley.

Budura, A., Michel, S., Cudré-Mauroux, P., Aberer, K. (2009). Neighborhood-based tag prediction. In Proceedings of 6th European semantic web conference (pp. 608–622). Berlin: Springer-Verlag.

Bu, J., Tan, S., Chen, C., Wang, C., Wu, H., Zhang, L., et al. (2010). Music recommendation by unified hypergraph: Combining social media information and music content. In Proceedings of the international conference on multimedia (pp. 391–400). New York: ACM.

Cantador, I., Brusilovsky, P., Kuflik, T. (2011). Second workshop on information heterogeneity and fusion in recommender systems. In Proceedings of the fifth ACM conference on recommender systems (pp. 387–388). New York: ACM.CrossRef

Demsar, J. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7, 1–30.MathSciNetMATH

Foster, K., Muth, S., Potterat, J., Rothenberg, R. (2001). A faster Katz status score algorithm. Computational & Mathematical Organization Theory, 7(4), 275–285.CrossRef

Font, F., Serra, J., Serra, X. (2012). Folksonomy-based tag recommendation online audio clip sharing. In Proceedings of 13th international conference on music information retrieval (ISMIR) (pp. 73–78).

Gemmell, J., Schimoler, T., Ramezani, M., Mobasher, B. (2009). Adapting k-nearest neighbor for tag recommendation in folksonomies. In Proceedings of the 7th workshop on intelligent techniques for web personalization & recommender systems.

Gemmell, J., Schimoler, T., Ramezani, M., Mobasher, B., Burke, R. (2011). Tag-based resource recommendation in social annotation applications. In Proceedings of the 6th European semantic web conference on the semantic web: research and applications (pp. 195–206). Berlin: Springer-Verlag.

Guan, Z., Bu, J., Mei, Q., Chen, C., Wang, C. (2009). Personalized tag recommendation using graph-based ranking on multi-type interrelated objects. In Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval (pp. 540–547). New York: ACM.

Hamouda, S., & Wanas, N. (2011). PUT-Tag: personalized user-centric tag recommendation for social bookmarking systems. Social Network Analysis and Mining, 1(4), 377–385.CrossRef

Horsburgh, B., Craw, S., Massie, S., Boswell, R. (2011). Finding the hidden gems: Recommending untagged music. In Proceedings of 22nd international joint conference on artificial intelligence - volume three (pp. 2256–2261). AAAI Press.

Hotho, A., Jäschke, R., Schmitz, C., Stumme, G. (2006). Information retrieval in folksonomies: Search and ranking. In Proceedings of the 3rd European semantic web conference (pp. 411–426). Berlin: Springer-Verlag.

Huang, Z., Li, X., Chen, H. (2005). Link prediction approach to collaborative filtering. In Proceedings of the 5th ACM/IEEE-CS joint conference on digital libraries (pp. 141–142). New York: ACM.CrossRef

Jäschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G. (2008). Tag recommendations in social bookmarking systems. AI Communications, 21(4), 231–247.MathSciNetMATH

Katz, L. (1953). A new status index derived from sociometric analysis. Psychometrika, 18(1), 39–43.MATHCrossRef

Krestel, R., Fankhauser, P., Nejdl, W. (2009). Latent dirichlet allocation for tag recommendation. In Proceedings of the third ACM conference on recommender systems (pp. 61–68). New York: ACM.CrossRef

Levy, M., & Sandler, M. (2009). Music information retrieval using social tags and audio. IEEE Transactions on Multimedia, 11(3), 383–395.CrossRef

Liben-Nowell, D., & Kleinberg, J. (2007). The link-prediction problem for social networks. Journal of the American Society for Information Science and Technology, 58(7), 1019–1031.CrossRef

Lipczak, M., & Milios, E. (2010). Learning in efficient tag recommendation. In Proceedings of the fourth ACM conference on recommender systems (pp. 167–174). New York: ACM.CrossRef

Liu, D., Hua, X.S., Yang, L., Wang, M., Zhang, H.J. (2009). Tag ranking. In Proceedings of the 18th international conference on world wide web (pp. 351–360). New York: ACM.CrossRef

Miotto, R., & Orio, N. (2012). A probabilistic model to combine tags and acoustic similarity for music retrieval. ACM Transactions on Information Systems, 30(2), 1–29, article no. 8.CrossRef

Ramezani, M. (2011). Improving graph-based approaches for personalized tag recommendation. Journal of Emerging Technologies in Web Intelligence, 3(2), 168–176.MathSciNetCrossRef

Rendle, S., & Schmidt-Thieme, L. (2010). Pairwise interaction tensor factorization for personalized tag recommendation. In Proceedings of the 3rd international conference on web search and web data mining (pp. 81–90). New York: ACM.CrossRef

Song, Y., Zhang, L., Giles, C. (2011). Automatic tag recommendation algorithms for social recommender systems. ACM Transaction on the Web, 5(1), 1–31.CrossRef

Sparck Jones, K., Walker, S., Robertson, S.E. (2000). A probabilistic model of information retrieval: development and comparative experiments. Information Processing and Management, 36(6), 809–840.CrossRef

Symeonidis, P., Ruxanda, M., Nanopoulos, A., Manolopoulos, Y. (2008). Ternary semantic analysis of social tags for personalized music recommendation. In Proceedings of 9th International conference on Music Information Retrieval (ISMIR) (pp. 219–224).

Tatli, I., & Birturk, A. (2011). A tag-based hybrid music recommendation system using semantic relations and multi-domain information. In Proceedings of IEEE 11th international conference on data mining workshops (ICDMW) (pp. 548–554).

Vallet, D., Cantador, I., Joemon, J. (2010). Personalizing web search with folksonomy-based user and document profiles. In Proceedings of the 32nd European conference on advances in information (pp. 420–431). Berlin: Springer-Verlag.

Wetzker, R., Zimmermann, C., Bauckhage, C., Albayrak, S. (2010). I tag, you tag: Translating tags for advanced user models. In Proceedings of the 3rd ACM international conference on web search and data mining (pp. 71–80). New York: ACM.CrossRef

Xu, S., Bao, S., Fei, B., Su, Z., Yu, Y. (2008). Exploring folksonomy for personalized search. In Proceedings of 31st annual international ACM SIGIR conference (pp. 155–162). New York: ACM.

Zanardi, V., & Capra, L. (2008). Social ranking: Uncovering relevant content using tag-based recommender systems. In Proceedings of 2nd ACM conference on recommender systems (pp. 51–58). New York: ACM.

Title: Folksonomy link prediction based on a tripartite graph for tag recommendation
Authors: Majdi Rawashdeh
Heung-Nam Kim
Jihad Mohamad Alja’am
Abdulmotaleb El Saddik
Publication date: 01-04-2013
Publisher: Springer US
Published in: Journal of Intelligent Information Systems / Issue 2/2013
Print ISSN: 0925-9902
Electronic ISSN: 1573-7675
DOI: https://doi.org/10.1007/s10844-012-0227-2

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 2/2013

Iterative classification for multiple target attributes

Meme ranking to maximize posts virality in microblogging platforms

Toward finding hidden communities based on user profile

Catching a viral video

Tag recommendation by machine learning with textual and social features

Special issue on SIASP at ICDM 2010

Premium Partner