An Information Extraction Support System from BBS Using Topic Mapping Based on Structure of Conversation with a 3-dimensional Space

This paper proposes a support system for the information extraction from BBS (Bulletin Board System). On BBS in EC (Electronic Commerce) sites, participants who are consumers write frank opinions easily. This produces active conversation as enormous text data and includes unexpected opinions and consumers' requirements. In this system, opinions on BBS are classified by topics and arranged on a 3-dimensional space so that users (for example product designers) can easily understand how topics are interwoven into conversations or how topics are related to each other. Furthermore, two methods using the feature of the conversation structure on BBS are proposed for correcting the recognition of opinions.