Abstract
Mobile search market is growing very fast. Mining mobile search activities is helpful for understanding user preference, interest and even regular patterns. In previous works, text information contained by either search queries or web pages visited by users is well studied to mine search activities. Since rich context information (e.g., time, location and other sensor inputs) is contained in the mobile search data, it has also been leveraged by researchers for mining user activities. However, the two types of information were used separately. In this paper, we propose a graphical model approach, namely the Text and Context-based User Activity Model (TCUAM), which mines user activity patterns by utilizing query text and context simultaneously. The model is developed based on Latent Dirichlet Allocation (LDA) by regarding users’ activities as latent topics. In order to guide the activity mining process, we borrow some external knowledge of topic-word relationship to build a constrained TCUAM model. The experimental results indicate that the TCUAM model yields better results compared with text-only and context-only approaches. We also find that the constrained TCUAM model is more effective than the unconstrained TCUAM model.
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References
Wagner, M., Balke, W.-T., Hirschfeld, R., Kellerer, W.: A Roadmap to Advanced Personalization of Mobile Services. In: Proceedings of the DOA/ODBASE/CoopIS, Industry Program (2002)
Sieg, A., Mobasher, B., Burke, R.: Web Search Personalization with Ontological User Profiles. In: Proceedings of CIKM 2007 (2007)
Bao, T., Cao, H., Chen, E., Tian, J., Xiong, H.: An Unsupervised Approach to Modeling Personalized Contexts of Mobile Users. In: Proceedings of ICDM 2010 (2010)
Noll, M.G., Meinel, C.: Web Search Personalization Via Social Bookmarking and Tagging. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 367–380. Springer, Heidelberg (2007)
Teevan, J., Dumais, S.T., Horvitz, E.: Personalizing Search via Automated Analysis of Interests and Activities. In: Proceedings of SIGIR 2005 (2005)
Arias, M., Cantera, J.M.: Context-based Personalization for Mobile Web Search. In: Proceedings of VLDB 2008 (2008)
Hattori, S., Tezuka, T., Tanaka, K.: Context-Aware Query Refinement for Mobile Web Search. In Proceedings of SAINT-W 2007 (2007)
Church, K., Smyth, B.: Who, What, Where & When: A New Approach to Mobile Search. In: Proceedings of IUI 2008 (2008)
Gregory, D.A., Atkeson, C.G., Hong, J., Long, S.: Kooper,R, Pinkerton, R.: Cyberguide: A Mobile Context-Aware Tour Guide. Wireless Networks (1997)
Ozturk, P., Aamodt, A.: Towards a Model of Context for Case-based Diagnostic Problem Solving. In: Proceedings of CONTEXT 1997 (1997)
Schilit, B., Adams, N., Want, R.: Context-Aware Computing Applications. In: Proceedings of the Workshop on Mobile Computing Systems and Applications (1994)
Liao, L., Patterson, D. J., Fox, D., Kautz, H.: Building Personal Maps from GPS Data. In: Proceedings of IJCAI Workshop on Modeling Others from Observation (2005)
Darnell, M.H.H., Moore, J., Essa, I.A.: Exploiting Human Actions and Object Context for Recognition Tasks. In: Proceedings of ICCV 1999 (1999)
Heinrich, G.: Parameter Estimation for Text Analysis. Technical Report (2004)
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Peng, B., Wang, Y., Sun, JT. (2012). Mining Mobile Users’ Activities Based on Search Query Text and Context. In: Tan, PN., Chawla, S., Ho, C.K., Bailey, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2012. Lecture Notes in Computer Science(), vol 7302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30220-6_10
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DOI: https://doi.org/10.1007/978-3-642-30220-6_10
Publisher Name: Springer, Berlin, Heidelberg
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