An effective approach to document retrieval via utilizing WordNet and recognizing phrases
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
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
Computational Linguistics
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
HAWK: A Focused Crawler with Content and Link Analysis
ICEBE '08 Proceedings of the 2008 IEEE International Conference on e-Business Engineering
Proximity-based opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Extracting informative textual parts from web pages containing user-generated content
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
An Agent-Based Focused Crawling Framework for Topic- and Genre-Related Web Document Discovery
ICTAI '12 Proceedings of the 2012 IEEE 24th International Conference on Tools with Artificial Intelligence - Volume 01
Sentiment analysis of user comments for one-class collaborative filtering over ted talks
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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The constantly increasing amount of opinionated texts found in the Web had a significant impact in the development of sentiment analysis. So far, the majority of the comparative studies in this field focus on analyzing fixed (offline) collections from certain domains, genres, or topics. In this paper, we present an online system for opinion mining and retrieval that is able to discover up-to-date web pages on given topics using focused crawling agents, extract opinionated textual parts from web pages, and estimate their polarity using opinion mining agents. The evaluation of the system on real-world case studies, demonstrates that is appropriate for opinion comparison between topics, since it provides useful indications on the popularity based on a relatively small amount of web pages. Moreover, it can produce genre-aware results of opinion retrieval, a valuable option for decision-makers.