Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Interactive multimedia summaries of evaluative text
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Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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Proceedings of the 17th international conference on World Wide Web
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Pulse: mining customer opinions from free text
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Selecting a characteristic set of reviews
Proceedings of the 18th 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
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Generating comparative summaries from reviews
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Proceedings of the 23rd international conference on World wide web
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This paper proposes a method to extract product features from user reviews and generate a review summary. This method only relies on product specifications, which usually are easy to obtain. Other resources like segmenter, POS tagger or parser are not required. At feature extraction stage, multiple specifications are clustered to extend the vocabulary of product features. Hierarchy structure information and unit of measurement information are mined from the specification to improve the accuracy of feature extraction. At summary generation stage, hierarchy information in specifications is used to provide a natural conceptual view of product features.