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Author-Topic over Time (AToT): A Dynamic Users’ Interest Model

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Book cover Mobile, Ubiquitous, and Intelligent Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 274))

Abstract

One of the key problems in upgrading information services towards knowledge services is to automatically mine latent topics, users’ interests and their evolution patterns from large-scale S&T literatures. Most of current methods are devoted to either discover static latent topics and users’ interests, or to analyze topic evolution only from intra-features of documents, namely text content without considering directly extra-features of documents such as authors. To overcome this problem, a dynamic users’ interest model for documents using authors and topics with timestamps is proposed, named as Author-Topic over Time (AToT) model, and collapsed Gibbs sampling method is utilized for inferring model parameters. This model is not only able to discover latent topics and users’ interests, but also to mine their changing patterns over time. Finally, the extensive experimental results on NIPS dataset with 1,740 papers indicate that our AToT model is feasible and efficient.

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References

  1. Qiu, F., Cho, J.: Automatic identification of user interest for personalized search. In: WWW 2006, pp. 727–736. ACM, New York (2006)

    Google Scholar 

  2. Kim, J., Jeong, D.H., Lee, D., Jung, H.: User-centered innovative technology analysis and prediction application in mobile environment. Multimed. Tools Appl. (2013)

    Google Scholar 

  3. Rosen-Zvi, M., Chemudugunta, C., Griffiths, T., Smyth, P., Steyvers, M.: Learning author-topic models from text corpora. ACM T. Inform. Syst. 28(1), 1–38 (2010)

    Article  Google Scholar 

  4. McCallum, A., Wang, X., Corrada-Emmanuel, A.: Topic and role discovery in socail networks with experiments on enron and academic email. J. Artif. Intell. Res. 30(1), 249–272 (2007)

    Google Scholar 

  5. Mimno, D., McCallum, A.: Expertise modeling for matching papers with reviewers. In: KDD 2007, pp. 500–509. ACM, New York (2007)

    Google Scholar 

  6. Kawamae, N.: Author interest topic model. In: SIGIR 2010, pp. 887–888. ACM, New York (2010)

    Google Scholar 

  7. Kawamae, N.: Latent interest-topic model: Finding the causal relationships behind dyadic data. In: CIKM 2010, pp. 649–658. ACM, New York (2010)

    Google Scholar 

  8. Tang, J., Zhang, J., Jin, R., Yang, Z., Cai, K., Zhang, L., Su, Z.: Topic level expertise search over heterogeneous networks. Mach. Learn. 82(2), 211–237 (2011)

    Article  Google Scholar 

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

    Google Scholar 

  10. Wang, X., Mohanty, N., McCallum, A.: Group and topic discovery from relations and their attributes. In: Weiss, Y., Schölkopf, B., Platt, J. (eds.) NIPS18, pp. 1449–1456. MIT Press, Cambridge (2006)

    Google Scholar 

  11. Wang, X., McCallum, A.: Topics over time: A non-Markov continuous-time model of topical trends. In: KDD 2006, pp. 424–433. ACM, New York (2006)

    Google Scholar 

  12. Xu, S., Zhu, L., Qiao, X., Shi, Q., Gui, J.: Topic linkages between papers and patents. In: AST 2012. SERSC, pp. 176–183. Daejeon, South Korea (2012)

    Google Scholar 

  13. Blei, D.M., Lafferty, J.D.: Dynamic topic models. In: ICML 2006, pp. 113–120. ACM, New York (2006)

    Google Scholar 

  14. Wang, C., Blei, D., Heckerman, D.: Continuous time dynamic topic models. In: UAI 2008, pp. 579–586 (2008)

    Google Scholar 

  15. Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci. USA 101(suppl. 1), 5228–5235 (2004)

    Article  Google Scholar 

  16. Owen, C.B.: Parameter estimation for the Beta distribution. Master’s thesis, Brigham Young University (2008)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Information Technology Supporting Center, Institute of Scientific and Technical Information of China, No. 15 fuxing Rd., Haidian District, Beijing, 100038, P.R. China

    Shuo Xu, Qingwei Shi & Lijun Zhu

  2. School of Software, Liaoning Technical University, No. 188 Longwan St. South, Huludao, Liaoning, 125105, P.R. China

    Qingwei Shi

  3. College of Software, Northeast Normal University, 5268 Renmin St., Changchun, Jilin, 130024, P.R. China

    Xiaodong Qiao

  4. Department of Computer Intelligence Research, Korea Institute of Science and Technology Information, 245 Daehak-ro, Yuseong-gu, Daejeon, 305-806, Korea

    Hanmin Jung, Seungwoo Lee & Sung-Pil Choi

Authors
  1. Shuo Xu
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  2. Qingwei Shi
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  3. Xiaodong Qiao
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  4. Lijun Zhu
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  5. Hanmin Jung
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  6. Seungwoo Lee
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  7. Sung-Pil Choi
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Corresponding author

Correspondence to Shuo Xu .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Biomedical Informatics Neuroscience, Ohio State University Center for Biomedical Engineering, Columbus, Ohio, USA

    Hojjat Adeli

  3. Dept of Computer Education, Jeju National University Teachers College, Jeju Special Self-Governing Province, Korea, Republic of (South Korea)

    Namje Park

  4. Ryerson University Dept. Computer Science, Toronto, Ontario, Canada

    Isaac Woungang

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© 2014 Springer-Verlag Berlin Heidelberg

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Xu, S. et al. (2014). Author-Topic over Time (AToT): A Dynamic Users’ Interest Model. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_37

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  • DOI: https://doi.org/10.1007/978-3-642-40675-1_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40674-4

  • Online ISBN: 978-3-642-40675-1

  • eBook Packages: EngineeringEngineering (R0)

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