An Outdoor Recommendation System based on User Location History

Recommendation systems, which automatically understand user preferences and make recommendations, are now widely used in online shopping. However, so far there have been few attempts of applying them to real-world shopping. In this paper, we propose a novel real-world recommendation system, which makes recommendations of shops based on users’ past location data history. The system uses a newly devised place learning algorithm, which can efficiently find users’ frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”). Users’ frequented shops are used as input to the item-based collaborative filtering algorithm to make recommendations. In addition, we provide a method for further narrowing down shops based on prediction of user movement and geographical conditions of the city. We have evaluated our system at a popular shopping district inside Tokyo, and the results demonstrate the effectiveness of our overall approach.

[1]  Mauro Brunato,et al.  A Location-Dependent Recommender System for the Web , 2002 .

[2]  Chris Schmandt,et al.  Location-Aware Information Delivery with ComMotion , 2000, HUC.

[3]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[4]  Thad Starner,et al.  Learning Significant Locations and Predicting User Movement with GPS , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[5]  Katia P. Sycara,et al.  WebMate: a personal agent for browsing and searching , 1998, AGENTS '98.

[6]  Andy Hopper,et al.  A new location technique for the active office , 1997, IEEE Wirel. Commun..

[7]  Dharma P. Agrawal,et al.  Jini Home Networking: A Step toward Pervasive Computing , 2002, Computer.

[8]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[9]  Bill N. Schilit,et al.  Place Lab: Device Positioning Using Radio Beacons in the Wild , 2005, Pervasive.

[10]  Johan Himberg,et al.  Collaborative context recognition for handheld devices , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[11]  Bill N. Schilit,et al.  An overview of the PARCTAB ubiquitous computing experiment , 1995, IEEE Wirel. Commun..

[12]  Shashi Shekhar,et al.  Discovering personal gazetteers: an interactive clustering approach , 2004, GIS '04.

[13]  Bill N. Schilit,et al.  The Parctab Ubiquitous Computing Experiment , 1994, Mobidata.

[14]  Gregory D. Abowd,et al.  Cyberguide: A mobile context‐aware tour guide , 1997, Wirel. Networks.

[15]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[16]  Joo-Hyeon Lee,et al.  Implementation of new services to support ubiquitous computing for town life , 2005, Third IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems (SEUS'05).

[17]  Paramvir Bahl,et al.  A Software System for Locating Mobile Users: Design, Evaluation, and Lessons , 2000 .

[18]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[19]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

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

[21]  Werner Retschitzegger,et al.  Context-awareness on mobile devices - the hydrogen approach , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[22]  Patrick Brézillon.  Focusing on Context in Human-Centered Computing , 2003, IEEE Intell. Syst..

[23]  Seong-Woon Kim,et al.  Implementation of new services to support ubiquitous computing for campus life , 2004 .

[24]  Erik Guttman,et al.  Service Location Protocol: Automatic Discovery of IP Network Services , 1999, IEEE Internet Comput..

[25]  Ken Lang,et al.  NewsWeeder: Learning to Filter Netnews , 1995, ICML.

[26]  Abhaya Asthana,et al.  An Indoor Wireless System for Personalized Shopping Assistance , 1994, 1994 First Workshop on Mobile Computing Systems and Applications.

[27]  Bill N. Schilit,et al.  Context-aware computing applications , 1994, Workshop on Mobile Computing Systems and Applications.