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Semantic Grounding of Hybridization for Tag Recommendation

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Web-Age Information Management (WAIM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6184))

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Abstract

Tag recommendation for new resources is one of the most important issues discussed recently. Many existing approaches ignore text semantics and can not recommend new tags which are not in the training dataset (e.g., FolkRank). Some exceptional semantic approaches use a probabilistic latent semantic method to recommend tags in terms of topic knowledge (e.g., ACT model). However, they do not perform well because many entities in these models result in much noise. In this paper, we propose hybrid approaches in folksonomy to challenge these problems. Hybrid approaches are combination of Language Model (LM) for keyword based approach and Latent Dirichlet Allocation (LDA), Tag-Topic (TT) model and User-Tag-Topic (UTT) model for topic based approaches. Our approaches can recommend meaningful tags and can be used to discover resource implicit correlations. Experimental results on Bibsonomy dataset show that LM performs better than all other hybrid and non-hybrid approaches. Also the hybrid approaches with less number of entities (e.g., LDA with only one entity) perform better than those approaches having more entities (e.g., UTT with three entities) for tag recommendation task.

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References

  1. Lipczak, M.: Tag recommendation for folksonomies oriented towards individual users. In: ECML PKDD Discovery Challenge, pp. 84–95 (2008)

    Google Scholar 

  2. Hsu, M., Chen, H.: A method to predict social annotations. In: CIKM, pp. 1375–1376 (2008)

    Google Scholar 

  3. Jäschke, R., Marinho, L.B., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag recommendations in folksonomies. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) PKDD 2007. LNCS (LNAI), vol. 4702, pp. 506–514. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Mishne, G.: Autotag: a collaborative approach to automated tag assignment for weblog posts. In: WWW, pp. 953–954 (2006)

    Google Scholar 

  5. Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Folkrank: A ranking algorithm for folksonomies. In: LWA, pp. 111–114 (2006)

    Google Scholar 

  6. Sood, S., Owsley, S., Hammond, K., Birnbaum, L.: Tagassist: Automatic tag suggestion for blog posts. In: ICWSM (2007)

    Google Scholar 

  7. Tatu, M., Srikanth, M., DSilva, T.: Tag recommendations using bookmark content. In: RSDC, pp. 96–107 (2008)

    Google Scholar 

  8. Zhang, N., Zhang, Y., Tang, J.: A tag recommendation system based on contents. In: RSDC (2008)

    Google Scholar 

  9. Chen, Z., Cao, J., Song, Y., Guo, J., Zhang, Y., Li, J.: Context-oriented web video tag recommendation. In: WWW (to appear, 2010)

    Google Scholar 

  10. Daud, A., Li, J., Zhou, L., Muhammad, F.: A generalized topic modeling approach for maven search. In: Li, Q., Feng, L., Pei, J., Wang, S.X., Zhou, X., Zhu, Q.-M. (eds.) APWeb/WAIM 2009. LNCS, vol. 5446, pp. 138–149. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  11. Wei, X., Croft, W.B.: Lda-based document models for ad-hoc retrieval. In: SIGIR, pp. 178–185 (2006)

    Google Scholar 

  12. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. In: NIPS, pp. 601–608 (2001)

    Google Scholar 

  13. Steyvers, M., Smyth, P., Rosen-Zvi, M., Griffiths, T.L.: Probabilistic author-topic models for information discovery. In: KDD, pp. 306–315 (2004)

    Google Scholar 

  14. Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., Su, Z.: Arnetminer: extraction and mining of academic social networks. In: KDD, pp. 990–998 (2008)

    Google Scholar 

  15. Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., Su, Z.: Optimizing web search using social annotations. In: WWW, pp. 501–510 (2007)

    Google Scholar 

  16. Halpin, H., Robu, V., Shepherd, H.: The complex dynamics of collaborative tagging. In: WWW, pp. 211–220 (2007)

    Google Scholar 

  17. Sigurbjörnsson, B., van Zwol, R.: Flickr tag recommendation based on collective knowledge. In: WWW, pp. 327–336 (2008)

    Google Scholar 

  18. Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Mining association rules in folksonomies. In: IFCS, pp. 261–270 (2006)

    Google Scholar 

  19. Ruch, P., Baud, R.H., Geissbühler, A.: Evaluating and reducing the effect of data corruption when applying bag of words approaches to medical records. I. J. Medical Informatics 67(1-3), 75–83 (2002)

    Article  Google Scholar 

  20. Zhai, C., Lafferty, J.D.: A study of smoothing methods for language models applied to ad hoc information retrieval. In: SIGIR, pp. 334–342 (2001)

    Google Scholar 

  21. Lesot, M.J., Mouillet, L., Bouchon-Meunier, B.: Fuzzy prototypes based on typicality degrees. In: Fuzzy Days, pp. 125–138 (2004)

    Google Scholar 

  22. Hofmann, T.: Probabilistic latent semantic analysis. In: UAI, pp. 289–296 (1999)

    Google Scholar 

  23. Griffiths, T., Steyvers, M.: Finding scientific topics. PNAS 101, 5228–5235 (2004)

    Article  Google Scholar 

  24. Azzopardi, L., Girolami, M., van Rijsbergen, K.: Investigating the relationship between language model perplexity and ir precision-recall measures. In: SIGIR, pp. 369–370 (2003)

    Google Scholar 

  25. Daud, A., Li, J., Zhou, L., Muhammad, F.: Knowledge discovery through parametric directed probabilistic topic models. Journal of Frontiers of Computer Science in China (2009)

    Google Scholar 

  26. Chen, W., Chu, J.C., Luan, J., Bai, H., Wang, Y., Chang, E.Y.: Collaborative filtering for orkut communities: discovery of user latent behavior. In: WWW, pp. 681–690 (2009)

    Google Scholar 

  27. Rosen-Zvi, M., Griffiths, T.L., Steyvers, M., Smyth, P.: The author-topic model for authors and documents. In: UAI, pp. 487–494 (2004)

    Google Scholar 

  28. Jarvelin, K., Kekalainen, J.: Cumulated gain-based evaluation of IR techniques. ACM TOIS 4(20), 422–446 (2002)

    Article  Google Scholar 

  29. Koren, Y.: Factorization meets the neighborhood: a multifaceted collaborative filtering model. In: KDD, pp. 426–434 (2008)

    Google Scholar 

  30. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Syst. Man Cybern. 18(1), 183–190 (1988)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Yan’an Jin, Ruixuan Li & Yuhua Li

  2. School of Information and Management, Hubei University of Economics, Wuhan, 430205, China

    Yan’an Jin

  3. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Yi Cai & Qing Li

  4. Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Ali Daud

Authors
  1. Yan’an Jin
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  2. Ruixuan Li
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  3. Yi Cai
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  4. Qing Li
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  5. Ali Daud
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  6. Yuhua Li
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

    Lei Chen

  2. Computer Department, Sichuan University, 610064, Chengdu, China

    Changjie Tang

  3. Department of Computer Science, Duke University, Box 90129, NC 27708-0129, Durham, USA

    Jun Yang

  4. College of Computer Science, Zhejiang University, 388 Yuhangtang Road, 310058, Hangzhou, China

    Yunjun Gao

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© 2010 Springer-Verlag Berlin Heidelberg

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Jin, Y., Li, R., Cai, Y., Li, Q., Daud, A., Li, Y. (2010). Semantic Grounding of Hybridization for Tag Recommendation. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds) Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14246-8_16

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  • DOI: https://doi.org/10.1007/978-3-642-14246-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14245-1

  • Online ISBN: 978-3-642-14246-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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