MCORE: a context-sensitive recommendation system for the mobile Web

: Recommendation systems for the mobile Web have focused on endorsing particular types of content to users. Today, mobile service providers have a more direct recommendation channel, namely the short messaging service. Therefore, mobile service providers should consider both the timing and context of recommendation messages (push messages) that are sent to users. Mobile service providers can learn context-specific user preferences by analysing mobile Web use logs and user responses to push messages. In this paper, we present a context-sensitive recommendation system that can be used to select the optimal context in which to send recommendation messages. We call this system the mobile context recommender system (MCORE). We compared user responses to push messages delivered in and out of suitable contexts as determined by MCORE. The precision of push messages delivered within a suitable context was higher than that of messages delivered outside of one.

[1]  Gediminas Adomavicius,et al.  Incorporating contextual information in recommender systems using a multidimensional approach , 2005, TOIS.

[2]  Sergio A. Alvarez,et al.  Efficient Adaptive-Support Association Rule Mining for Recommender Systems , 2004, Data Mining and Knowledge Discovery.

[3]  Peter Steenkiste,et al.  Avoiding Privacy Violations Caused by Context-Sensitive Services , 2006, PerCom.

[4]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[5]  Keith Cheverst,et al.  Developing a context-aware electronic tourist guide: some issues and experiences , 2000, CHI.

[6]  Soe-Tsyr Yuan,et al.  A recommendation mechanism for contextualized mobile advertising , 2003, Expert Syst. Appl..

[7]  Peter J. Brown,et al.  Context-aware applications: from the laboratory to the marketplace , 1997, IEEE Wirel. Commun..

[8]  Richard Hull,et al.  Towards situated computing , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[9]  Jason Pascoe,et al.  The stick-e note architecture: extending the interface beyond the user , 1997, IUI '97.

[10]  Marco Gruteser,et al.  A Methodological Assessment of Location Privacy Risks in Wireless Hotspot Networks , 2003, SPC.

[11]  Chan Young Kim,et al.  VISCORS: a visual-content recommender for the mobile Web , 2004, IEEE Intelligent Systems.

[12]  Johan Koolwaaij,et al.  Context-Aware Recommendations in the Mobile Tourist Application COMPASS , 2004, AH.

[13]  Pattie Maes,et al.  Personalized location-based brokering using an agent-based intermediary architecture , 2003, Decis. Support Syst..

[14]  Eija Kaasinen,et al.  User needs for location-aware mobile services , 2003, Personal and Ubiquitous Computing.

[15]  Marco Gruteser,et al.  Wireless Location Privacy Protection , 2003, Computer.

[16]  Gerd Kortuem,et al.  Software organization for dynamic and adaptable wearable systems , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[17]  Gregory D. Abowd,et al.  Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.

[18]  John T. Stasko,et al.  Design iterations for a location-aware event planner , 2004, Personal and Ubiquitous Computing.

[19]  Lars Kulik,et al.  A Formal Model of Obfuscation and Negotiation for Location Privacy , 2005, Pervasive.

[20]  John Durkin,et al.  Expert Systems , 1994 .

[21]  Loren G. Terveen,et al.  Specifying preferences based on user history , 2002, CHI.

[22]  Jae Kyu Lee,et al.  VISCORS: A Visual-Content Recommender for the Mobile Web , 2004, IEEE Intell. Syst..

[23]  David A. Landgrebe,et al.  A survey of decision tree classifier methodology , 1991, IEEE Trans. Syst. Man Cybern..

[24]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[25]  Mauro Brunato,et al.  PILGRIM: A location broker and mobility-aware recommendation system , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[26]  Padraig Cunningham,et al.  Context boosting collaborative recommendations , 2004, Knowl. Based Syst..

[27]  Peter Steenkiste,et al.  Avoiding privacy violations caused by context-sensitive services , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM'06).

[28]  Von-Wun Soo,et al.  A personalized restaurant recommender agent for mobile e-service , 2004, IEEE International Conference on e-Technology, e-Commerce and e-Service, 2004. EEE '04. 2004.

[29]  Per Capita,et al.  About the authors , 1995, Machine Vision and Applications.

[30]  Jun Ozawa,et al.  Analysis of appropriate timing for information notification based on indoor user's location transition , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM'06).