Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Recognizing subjectivity: a case study in manual tagging
Natural Language Engineering
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Automatically refining the wikipedia infobox ontology
Proceedings of the 17th international conference on World Wide Web
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Easiest-first search: towards comprehension-based web search
Proceedings of the 18th ACM conference on Information and knowledge management
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Nowadays, many users create information related to user-generated content (UGC) such as that for social network services (SNSs). They create communities based on their hobbies and interests. Then they readily exchange that information mutually in the UGC. They know the information of the community deeply and the information tends to become rare information. Therefore, much information that is not written in the general Web content is buried in the UGC. We designate that buried information as "hidden information." Our proposed "hidden information" definition is "specific information for the community and important information for general users." As described in this paper, we propose a means to extract "hidden information."