出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we propose a constrained independent topic analysis in text mining. Independent topic analysis is a method for extracting mutually independent topics from the text data by using the independent component analysis. In the independent topic analysis, it is possible to obtain the most independent topics. However, these obtained topics may differ from the ones wanted by user. For example, it is assumed resultant three topics, topic A and topic B and topic C. If a content of topic A and topic B is thought to be close, user wants to merge the topic A and topic B as one of the topic D. In addition, when user wants to analyze topic A in more detail, user would like to separate topic A to topic E and topic F. In that case, method which can incorporate these requests of the user is required. To that end, we define the Merge Link constraints and Separate Link constraints. Merge Link constraints is a constraint that merges two topics in a single topic. Separate Link constraint is a constraint that separates one of the topics in the two topics. In this paper, we propose a method of obtaining a highly independent topic that meet these constraints. We conducted evaluation experiments on proposed methods, and obtained results to show the effectiveness of our approach.
