An algorithm for suffix stripping
Readings in information retrieval
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Product feature categorization with multilevel latent semantic association
Proceedings of the 18th ACM conference on Information and knowledge management
Multi-aspect opinion polling from textual reviews
Proceedings of the 18th ACM conference on Information and knowledge management
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Review recommendation: personalized prediction of the quality of online reviews
Proceedings of the 20th ACM international conference on Information and knowledge management
ETF: extended tensor factorization model for personalizing prediction of review helpfulness
Proceedings of the fifth ACM international conference on Web search and data mining
Bootstrapped named entity recognition for product attribute extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Expert Systems with Applications: An International Journal
On the design of LDA models for aspect-based opinion mining
Proceedings of the 21st ACM international conference on Information and knowledge management
The FLDA model for aspect-based opinion mining: addressing the cold start problem
Proceedings of the 22nd international conference on World Wide Web
Sentimental product recommendation
Proceedings of the 7th ACM conference on Recommender systems
Aspect-specific polarity-aware summarization of online reviews
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Topic extraction from online reviews for classification and recommendation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Mining customer reviews (opinion mining) has emerged as an interesting new research direction. Most of the reviewing websites such as Epinions.com provide some additional information on top of the review text and overall rating, including a set of predefined aspects and their ratings, and a rating guideline which shows the intended interpretation of the numerical ratings. However, the existing methods have ignored this additional information. We claim that using this information, which is freely available, along with the review text can effectively improve the accuracy of opinion mining. We propose an unsupervised method, called Opinion Digger, which extracts important aspects of a product and determines the overall consumer's satisfaction for each, by estimating a rating in the range from 1 to 5. We demonstrate the improved effectiveness of our methods on a real life dataset that we crawled from Epinions.com.