Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th 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
A Survey of Web Information Extraction Systems
IEEE Transactions on Knowledge and Data Engineering
Time period identification of events in text
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
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Internet users write blogs related to their personal experience, daily news, and so on. Though we can obtain blogs about personal experience using search engines on the Web, the search engines also output blogs about other topics unrelated to personal experiences. Therefore, we need to take too much time to read all blogs for obtaining those about personal experiences. This paper proposes a support system for obtaining blogs about personal experience efficiently. The system extracts three keywords that denote place, object , and action from a blog. The three keywords describe an event that leads a person to write a blog about personal experience. The system expresses the event with three pictures related to the extracted keywords. The pictures help users to judge whether personal experiences are written in the blog or not. We experimented with the system, and verified that it supports users to obtain personal experiences efficiently.