The purpose of this study is to examine cognition of principals about management of school libraries and roles of the teacher librarian in high schools by means of analyzing result of the questionnaire survey which was conducted by Professor Setsuko Koga and the author as a joint research in June of 2000. The questionnaires were sent to principals of all high schools that have a general course of full time in Tokyo, Osaka and Kyoto. The number of respondents was 271 and the reply rates were 40%. From this study, it was found that many principals were positive thinking to manage school libraries and evaluating roles of teacher librarians. But a few problems were found. The most serious problem is that they were negative thinking of the instructional role of the teacher librarian on joint curriculum planning with teachers in subject areas.
The purpose of this paper is to re-examine the text categorization research and discuss the future direction. Text categorization - the assignment of texts to predefined category based on their content - needs many procedures. The basic elements which constitute an automated text categorization are text structure, data size, feature extraction, feature selection, text representation, similarity measure, category representation, category assignment method, and evaluation method. Each element and relationships among the elements were clarified from the previous researches in text categorization. As the result, a) text structure and feature selection have big influence on the performance of text categorization, b) category representation and similarity measure have strong connection with each other, c) feature extraction which is important element is influenced by outside factor, but this method has big influence on the performance of text categorization. Furthermore, text categorization for Web pages is discussed. New problems with text structure and feature selection are addressed. Text structure becomes a more important element for improving the performance of text categorization. Feature selection has new problems, such as feature selection method for small size texts, in addition to existing ones.