Text databases & document management
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
A pitfall and solution in multi-class feature selection for text classification
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Neural Computation
Utility scoring of product reviews
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Proceedings of the 16th international conference on World Wide Web
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Seeing several stars: a rating inference task for a document containing several evaluation criteria
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Dialogue-oriented review summary generation for spoken dialogue recommendation systems
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Experiments on summary-based opinion classification
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Jointly modeling aspects and opinions with a MaxEnt-LDA hybrid
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
The bag-of-opinions method for review rating prediction from sparse text patterns
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
An assessment of machine learning techniques for review recommendation
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
Sentence based sentiment classification from online customer reviews
Proceedings of the 8th International Conference on Frontiers of Information Technology
Ontology-guided approach to feature-based opinion mining
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method
ACM Transactions on Management Information Systems (TMIS)
Selecting a characteristic set of reviews
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Making objective decisions from subjective data: Detecting irony in customer reviews
Decision Support Systems
Mining millions of reviews: a technique to rank products based on importance of reviews
Proceedings of the 13th International Conference on Electronic Commerce
Towards jointly extracting aspects and aspect-specific sentiment knowledge
Proceedings of the 21st ACM international conference on Information and knowledge management
Using micro-documents for feature selection: The case of ordinal text classification
Expert Systems with Applications: An International Journal
The FLDA model for aspect-based opinion mining: addressing the cold start problem
Proceedings of the 22nd international conference on World Wide Web
Hidden factors and hidden topics: understanding rating dimensions with review text
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
Sentiment classification of web review using association rules
OCSC'13 Proceedings of the 5th international conference on Online Communities and Social Computing
Topic extraction from online reviews for classification and recommendation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Robust multivariate autoregression for anomaly detection in dynamic product ratings
Proceedings of the 23rd international conference on World wide web
Feature selection for ordinal text classification
Neural Computation
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Online product reviews are becoming increasingly available, and are being used more and more frequently by consumers in order to choose among competing products. Tools that rank competing products in terms of the satisfaction of consumers that have purchased the product before, are thus also becoming popular. We tackle the problem of rating (i.e., attributing a numerical score of satisfaction to) consumer reviews based on their textual content. We here focus on multi-facet review rating, i.e., on the case in which the review of a product (e.g., a hotel) must be rated several times, according to several aspects of the product (for a hotel: cleanliness, centrality of location, etc.). We explore several aspects of the problem, with special emphasis on how to generate vectorial representations of the text by means of POS tagging, sentiment analysis, and feature selection for ordinal regression learning. We present the results of experiments conducted on a dataset of more than 15,000 reviews that we have crawled from a popular hotel review site.