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Improving Mobile Recommendations through Context-Aware User Interaction

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8538))

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Abstract

Mobile recommender systems provide personalized recommendations to help deal with today’s information overload. However, due to spatial limitations in mobile interfaces and uncertainty of the user’s preferences in the beginning, the improvement of the user experience remains one of the main challenges when designing these systems and has not been investigated thoroughly. This paper describes the aim and progress of the author’s PhD studies on the user interaction, usability and accuracy of mobile recommender systems. The approach aims to combine different user interaction methods with context-awareness to allow user-friendly personalized mobile recommendations.

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References

  1. Ricci, F.: Mobile Recommender Systems. Information Technology & Tourism 12(3), 205–231 (2010)

    Article  Google Scholar 

  2. Ricci, F.: Contextualizing Useful Recommendations. In: UMAP 2012 (2012), http://www.inf.unibz.it/~ricci/Slides/Context-UMAP-2012-Ricci.pdf

  3. Anand, S.S., Mobasher, B.: Contextual Recommendation. In: Berendt, B., Hotho, A., Mladenic, D., Semeraro, G. (eds.) WebMine 2007. LNCS (LNAI), vol. 4737, pp. 142–160. Springer, Heidelberg (2007)

    Google Scholar 

  4. Mcginty, L., Reilly, J.: On the Evolution of Critiquing Recommenders. In: Recommender Systems Handbook, pp. 419–453. Springer US (2011)

    Google Scholar 

  5. Rubens, N., Kaplan, D., Sugiyama, M.: Active Learning in Recommender Systems. In: Recommender Systems Handbook, pp. 735–767. Springer US (2011)

    Google Scholar 

  6. Rich, E.: User Modeling via Stereotypes. Cognitive Science 3(4), 329–354 (1979)

    Article  Google Scholar 

  7. Lamche, B., Trottmann, U., Woerndl, W.: Active Learning Strategies for Exploratory Mobile Recommender Systems. In: Proc. Decisions@CaRR workshop, 36th European Conference on Information Retrieval, Amsterdam, Netherlands (2014)

    Google Scholar 

  8. Na, Y., Agnhage, T.: Relationship between the preference styles of music and fashion and the similarity of their sensibility. International Journal of Clothing Science and Technology 25(2), 109–118 (2013)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Technische Universität München, Boltzmannstr. 3, 85748, Garching, Germany

    Béatrice Lamche

Authors
  1. Béatrice Lamche
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Editor information

Editors and Affiliations

  1. School of Computing, University of Leeds, United Kingdom

    Vania Dimitrova

  2. University of Haifa, Israel

    Tsvi Kuflik

  3. Department of Information and Computer Sciences, University of Hawaii, 96822, Honolulu, HI, USA

    David Chin

  4. Free University of Bozen - Bolzano, Piazza Domenicani 3, 39100, Bolzano, Italy

    Francesco Ricci

  5. Department of Computer Science, Aalborg University, Selma Lagerlofs Vej, 300 9220, Aalborg-East, Denmark

    Peter Dolog

  6. EEMCS - Web Information Systems, 2600 GA, Delft, The Netherlands

    Geert-Jan Houben

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© 2014 Springer International Publishing Switzerland

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Lamche, B. (2014). Improving Mobile Recommendations through Context-Aware User Interaction. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, GJ. (eds) User Modeling, Adaptation, and Personalization. UMAP 2014. Lecture Notes in Computer Science, vol 8538. Springer, Cham. https://doi.org/10.1007/978-3-319-08786-3_45

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  • DOI: https://doi.org/10.1007/978-3-319-08786-3_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08785-6

  • Online ISBN: 978-3-319-08786-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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