Paper: Personalized Recommendation of User Comments via Factor Models

ACL ID D11-1053
Title Personalized Recommendation of User Comments via Factor Models
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

In recent years, the amount of user-generated opinionated texts (e.g., reviews, user com- ments) continues to grow at a rapid speed: fea- tured news stories on a major event easily at- tract thousands of user comments on a popular online News service. How to consume subjec- tive information of this volume becomes an in- teresting and important research question. In contrast to previous work on review analysis that tried to filter or summarize information for a generic average user, we explore a dif- ferent direction of enabling personalized rec- ommendation of such information. For each user, our task is to rank the comments associated with a given article according to personalized user preference (i.e., whether the user is likely to like or dislike the comment). To this end, we propose a ...