Paper: Contextual Recommendation based on Text Mining

ACL ID C10-2079
Title Contextual Recommendation based on Text Mining
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

The potential benefit of integrating con- textual information for recommendation has received much research attention re- cently, especially with the ever-increasing interest in mobile-based recommendation services. However, context based recom- mendation research is limited due to the lack of standard evaluation data with con- textual information and reliable technol- ogy for extracting such information. As a result, there are no widely accepted con- clusions on how, when and whether con- text helps. Additionally, a system of- ten suffers from the so called cold start problem due to the lack of data for train- ing the initial context based recommenda- tion model. This paper proposes a novel solution to address these problems with automated information extraction tech- niques. We also comp...