Publication Type

Conference Proceeding Article

Publication Date

5-2005

Abstract

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our system is indeed able to learn both quickly and accurately.

Discipline

Databases and Information Systems

Research Areas

Information Systems and Management

Publication

Proceedings of the 6th International Conference on Mobile Data Management (MDM'05), Ayia Napa Cyprus, May 9 - 13

First Page

265

Last Page

272

Identifier

10.1145/1071246.1071289

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/1071246.1071289

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