Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Unsupervised named-entity extraction from the web: an experimental study
Artificial Intelligence
Just how mad are you? finding strong and weak opinion clauses
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Collecting evaluative expressions for opinion extraction
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Studying the effects of noisy text on text mining applications
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
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
Extracting service aspects from web reviews
WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
Selecting a comprehensive set of reviews
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
SumView: A Web-based engine for summarizing product reviews and customer opinions
Expert Systems with Applications: An International Journal
Aspect-specific polarity-aware summarization of online reviews
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
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Consumers have to often wade through a large number of on-line reviews in order to make an informed product choice. We introduce OPINE, an unsupervised, high-precision information extraction system which mines product reviews in order to build a model of product features and their evaluation by reviewers.