Advertisement

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

  • Rong Pan
  • Guandong Xu
  • Peter Dolog
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 114)

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.

keywords

Tag neighbors Recommender system Spectral clustering Social tagging 

References

  1. 1.
    Bayyapu KR, Dolog P (2010) Tag and neighbour based recommender system for medical events. In: Proceedings of MEDEX 2010: the first international workshop on web science and information exchange in the medical web colocated with WWW 2010 conference, 2010Google Scholar
  2. 2.
    Budura A, Michel S, Cudré-Mauroux P, Aberer K (2009) Neighborhood-based tag prediction. The semantic web: research and applications, pp 608–622Google Scholar
  3. 3.
    Chen H, Dumais S (2000) Bringing order to the web: automatically categorizing search results. In: CHI ’00: proceedings of the SIGCHI conference on human factors in computing systems, New York, NY, USA, ACM, pp 145–152Google Scholar
  4. 4.
    Hayes C, Avesani P (2007) Using tags and clustering to identify topic-relevant blogs. In: International conference on weblogs and social media, March 2007Google Scholar
  5. 5.
    Hotho A, Jäschke R, Schmitz C, Stumme G (2006) Folkrank: a ranking algorithm for folksonomies. In: Althoff K-D, Schaaf M (eds), LWA, Hildesheimer Informatik-Berichte, vol 1. University of Hildesheim, Institute of Computer Science, pp 111–114Google Scholar
  6. 6.
    Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):26113CrossRefGoogle Scholar
  7. 7.
    Pan R, Xu G, Dolog P (2010) User and document group approach of clustering in tagging systems. In: Proceeding of the 18th international workshop on personalization and recommendation on the web and beyond. LWA 2010Google Scholar
  8. 8.
    Xu G, Gu Y, Dolog P, Zhang Y, Kitsuregawa M (2011) Semrec: a semantic enhancement framework for tag based recommendation. In: Proceedings of twenty- fifth AAAI conference on artificial intelligence (AAAI-11), 2011Google Scholar
  9. 9.
    Xu G, Zong Y, Pan R, Dolog P, Jin P (2011) On kernel information propagation for tag clustering in social annotation systems. In: Proceeding of 15th international con- ference on knowledge-based and intelligent information and engineering systems (KES2011), 2011Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.Centre for Applied InformaticsVictoria UniversityMelbourneAustralia

Personalised recommendations