WordNet: a lexical database for English
Communications of the ACM
Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Generic text summarization using relevance measure and latent semantic analysis
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Text summarization via hidden Markov models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
Sentiment Mining in WebFountain
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
OPINE: extracting product features and opinions from reviews
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
Show me the money!: deriving the pricing power of product features by mining consumer reviews
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-document summarization using cluster-based link analysis
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
An integration strategy for mining product features and opinions
Proceedings of the 17th ACM conference on Information and knowledge management
Rated aspect summarization of short comments
Proceedings of the 18th international conference on World wide web
Marketing Science
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Comparative experiments on sentiment classification for online product reviews
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Document summarization using conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Manifold-ranking based topic-focused multi-document summarization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Mining user reviews: from specification to summarization
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
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
Pulse: mining customer opinions from free text
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
A fuzzy ontology and its application to news summarization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Multifaceted Perspective at Data Analysis: A Study in Collaborative Intelligent Agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
| Hi-index | 12.05 |
In this paper, we develop SumView, a Web-based review summarization system, to automatically extract the most representative expressions and customer opinions in the reviews on various product features. Different from existing review analysis which makes more efforts on sentiment classification and opinion mining, our system mainly focuses on summarization, i.e., delivering the majority of information contained in the review documents by selecting the most representative review sentences for each extracted product feature. Comprehensive case studies and experiments demonstrate the effectiveness of our system, and the user study shows users' satisfaction.