Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Open user profiles for adaptive news systems: help or harm?
Proceedings of the 16th international conference on World Wide Web
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
Modeling relationships at multiple scales to improve accuracy of large recommender systems
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Proceedings of the 25th international conference on Machine learning
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Matchbox: large scale online bayesian recommendations
Proceedings of the 18th international conference on World wide web
How opinions are received by online communities: a case study on amazon.com helpfulness votes
Proceedings of the 18th international conference on World wide web
Personalized recommendation on dynamic content using predictive bilinear models
Proceedings of the 18th international conference on World wide web
Regression-based latent factor models
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Which side are you on?: identifying perspectives at the document and sentence levels
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Get out the vote: determining support or opposition from congressional floor-debate transcripts
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Automatically assessing review helpfulness
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Factor in the neighbors: Scalable and accurate collaborative filtering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Recognizing stances in online debates
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Pairwise interaction tensor factorization for personalized tag recommendation
Proceedings of the third ACM international conference on Web search and data mining
Exploiting social context for review quality prediction
Proceedings of the 19th international conference on World wide web
Recognizing stances in ideological on-line debates
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Semi-supervised correction of biased comment ratings
Proceedings of the 21st international conference on World Wide Web
Multi-objective ranking of comments on web
Proceedings of the 21st international conference on World Wide Web
Care to comment?: recommendations for commenting on news stories
Proceedings of the 21st international conference on World Wide Web
LogUCB: an explore-exploit algorithm for comments recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
Connecting comments and tags: improved modeling of social tagging systems
Proceedings of the sixth ACM international conference on Web search and data mining
Topical organization of user comments and application to content recommendation
Proceedings of the 22nd international conference on World Wide Web companion
HeteroMF: recommendation in heterogeneous information networks using context dependent factor models
Proceedings of the 22nd international conference on World Wide Web
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In recent years, the amount of user-generated opinionated texts (e.g., reviews, user comments) continues to grow at a rapid speed: featured news stories on a major event easily attract thousands of user comments on a popular online News service. How to consume subjective information of this volume becomes an interesting 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 different direction of enabling personalized recommendation 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 factor model that incorporates rater-comment and rater-author interactions simultaneously in a principled way. Our full model significantly outperforms strong baselines as well as related models that have been considered in previous work.