出版社：The Japanese Society for Artificial Intelligence
摘要：We propose a method to extract a lot of correspondences between questions and answers from a Web message board automatically. We use Web message boards as information sources because Web messasge boards have a lot of articles posted by general users. We extract correspondences between questions and answers that can be used in question answering systems to support natural language sentence input. At first, our proposed method classifies messages of a Web message board into either questions or others. Next, our method extracts a set of root-node pairs from the thread tree of a Web message board, where we define the thread tree when the root is an article classified as a question, and nodes are articles classified as answer candidates. Our method finds correspondences between questions and answers using two clues, (1)similarity between their articles, (2)link count between their articles. We experimented the proposed method, discussed results, and analyzed errors.
关键词：question answering ; information extraction ; text mining
