Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Let's browse: a collaborative Web browsing agent
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
Information Filtering: Overview of Issues, Research and Systems
User Modeling and User-Adapted Interaction
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Mineração de opiniões aplicada à análise de investimentos
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
Sentiment classification using information extraction technique
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
The state-of-the-art in personalized recommender systems for social networking
Artificial Intelligence Review
An information theoretic approach to sentiment polarity classification
Proceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality
Deriving market intelligence from microblogs
Decision Support Systems
Sentiment analysis in Facebook and its application to e-learning
Computers in Human Behavior
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We propose a collaborative exploration system that helps users to explore recommendations from various viewpoints. Given ratings and reviews on movies from reviewers, the system provides “virtual reviewers” that represent particular viewpoints. Each virtual reviewer navigates the user by recommending and characterizing both movies and reviewers according to its viewpoint. We have developed a browsing method with virtual reviewers and visual interfaces.