A Study on Information Acquisition and Extraction from Dynamic Information Sources Based on Knowledge Discovery and Learning

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In this research project, we studied information extraction from information sources in the web environment and user-friendly data operation facilities based on knowledge discovery and machine learning techniques. The research results can be summarized as follows.1.Extraction of information from hidden web sites is important. We developed a scheme to extract new topic contents form hidden web sites including document databases.2.We developed some new information analysis methods. In particular, new methods for topic detection from text steams, outlier detection, and correlation analysis were developed.3.We studied information extraction from the web using classification techniques. In particular, a system for web information retrieval was developed which utilizes existing taxonomy hierarchies. We also developed a new web information extraction method which combines database-oriented focused crawling and information extraction from web pages.4.Basic schemes for information sharing in distributed environments were studied.5.We developed a knowledge discovery technique for rule mining from transaction databases containing noise.6.We developed a smart facility which automatically generates XML queries based on data manipulation examples given by a user.7.Basic schemes to map binary data in original information sources into XML views were developed.8. We studied system architecture which can integrate a variety of information extracted from different information sources taking properties of original sources into consideration.