The Ejaki Project: A Quality of Service Regulator for Citizens

What is the meaning of "place"? How to provide a citizen with the right information anywhere, anytime? How to stimulate the growth of a user community, thus enriching the system's potential and the quality of the services provided? In this paper, we propose to contribute to these issues according to the artificial intelligence (AI), ubiquitous systems and community dynamics perspectives. The way we envisaged to achieve these goals was by a system which consists of a rated POI (point of interest) sharing platform accessible by several kind of mobile devices that we describe here.

[1]  Czeslaw Danilowicz,et al.  Using User Profiles in Intelligent Information Retrieval , 2002, ISMIS.

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

[3]  Alois Ferscha,et al.  Pervasive Computing , 2004, Lecture Notes in Computer Science.

[4]  L. M. Ward,et al.  The behavioral component in the meaning of places , 1983 .

[5]  Xianghua Ding,et al.  Nomatic: Location By, For, and Of Crowds , 2006, LoCA.

[6]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[7]  Henry A. Kautz,et al.  Inferring High-Level Behavior from Low-Level Sensors , 2003, UbiComp.

[8]  A. Galloway.  Intimations of everyday life: Ubiquitous computing and the city , 2004 .

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

[10]  Frank Curtis Stevens,et al.  Knowledge-based assistance for accessing large, poorly structured information spaces , 1993 .

[11]  Russell Beale,et al.  Supporting social interaction with smart phones , 2005, IEEE Pervasive Computing.

[12]  Stefano Spaccapietra,et al.  Matching User's Semantics with Data Semantics in Location-Based Services , 2005, MCMP@MDM.

[13]  Fredrik Espinoza,et al.  GeoNotes: Social and Navigational Aspects of Location-Based Information Systems , 2001, UbiComp.

[14]  Liviu Iftode,et al.  Indoor Localization Using Camera Phones , 2006, Seventh IEEE Workshop on Mobile Computing Systems & Applications (WMCSA'06 Supplement).

[15]  B. Krämer.  Classification of generic places : explorations with implications for evaluation , 1995 .

[16]  John A. Flanagan.  An Unsupervised Learning Paradigm for Peer-to-Peer Labeling and Naming of Locations and Contexts , 2006, LoCA.

[17]  Dan Frankowski,et al.  An experiment in discovering personally meaningful places from location data , 2005, CHI Extended Abstracts.

[18]  Jeffrey Hightower,et al.  From Position to Place , 2003 .

[19]  Mike Y. Chen,et al.  Voting with your feet : An investigative study of the relationship between place visit behavior and preference , 2006 .

[20]  William W. Cohen,et al.  Recommendation as Classification: Using Social and Content-Based Information in Recommendation , 1998, AAAI/IAAI.

[21]  Henry A. Kautz,et al.  Learning and inferring transportation routines , 2004, Artif. Intell..

[22]  Mitchel Resnick,et al.  Folk computing: designing technology to support face-to-face community building , 2002 .

[23]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[24]  A. Nasipuri,et al.  Experimental Evaluation of an Angle Based Indoor Localization System , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[25]  Elaine Rich,et al.  User Modeling via Stereotypes , 1998, Cogn. Sci..

[26]  Hugo Liu,et al.  ConceptNet — A Practical Commonsense Reasoning Tool-Kit , 2004 .

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

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