Miyako Tanaka[1](miyako@ube-k.ac.jp)
Sanae Nakazono[2](b1835@sty.cc.yamaguchi-u.ac.jp)
Hiroshi Matsuno[2](matsuno@sci.yamaguchi-u.ac.jp)
Hideki Tsujimoto[3](ht@kdel.info.eng.osaka-cu.ac.jp)
Yasuhiko Kitamura[3](kitamura@info.eng.osaka-cu.ac.jp)
Satoru Miyano[4](miyano@ims.u-tokyo.ac.jp)
[1]Department of Business Administration, Ube National College of Technology,
2-14-1, Tokiwadai, Ube 755-8555, Japan
[2]Faculty of Science, Yamaguchi University, 1677-1 Yoshida, Yamaguchi 753-8512, Japan
[3]Faculty of Engineering, Osaka City University, 3-3-138 Sugimoto, Sumiyoshiku, Osaka 558-8585, Japan
[4]Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan
We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.