Compression-Based Averaging of Selective Naive Bayes Classifiers
The Journal of Machine Learning Research
Designing Specific Weighted Similarity Measures to Improve Collaborative Filtering Systems
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Mining the real-time web: A novel approach to product recommendation
Knowledge-Based Systems
Recommendation using textual opinions
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Recommender systems have become, like search engines, a tool that cannot be ignored by a website with a large selection of products, music, news or simply webpages. The performance of this kind of systems depends on a large amount of information. Meanwhile, the amount of information available in the Web is continuously growing. In this paper, we propose to provide recommendation from unstructured textual data. The method has two steps. First, subjective texts are labelled according to their expressed opinion. Second, the results are used to provide recommendations thanks to a collaborative filtering technique. We describe the complete processing chain and evaluate it.