In web applications, recommendation algorithms such like collaborative filtering techniques are widely accepted for web users. To apply the algorithms for physical world objects such as books, three problems arise. The first problem is, how to input user ratings for physical objects? The second problem is, how to measure user interests for physical objects? The third problem is, how to consider the relationship between physical objects and users based on their locations? In order to solve the problems, this paper proposes a physical objects recommender system for cell phone users, PORSCHE. As for the first problem, PORSCHE estimates the user ratings using user behaviors for physical objects. As for the second problem, PORSCHE changes the user ratings using both user behaviors and elapsed time. As for the third problem, PORSCHE adjusts the user ratings by continually monitoring the distance between physical objects and users. The result of experiments simulating a bookstore shows that PORSCHE detects user interests accurately and it also recommends proper books for the user.
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2006 Dec 1|
|Event||2nd International Workshop on Personalized Context Modeling and Management for UbiComp Applications , ubiPCMM 2006 - Orange County, CA, United States|
Duration: 2006 Sep 17 → 2006 Sep 21
ASJC Scopus subject areas
- Computer Science(all)