AUTOMATIC THESAURUS GENERATION FOR AN ELECTRONIC COMMUNITY SYSTEM

This research reports an algorithmic approach to the automatic generat ion of thesauri for electronic community systems. The techniques used included term filtering, automatic indexing, and cluster analysis. The testbed for our research was the Worm Community System, which contain s a comprehensive library of specialized community data and literature , currently in use by molecular biologists who study the nematode worm C. elegans. The resulting worm thesaurus included 2709 researchers' n ames, 798 gene names, 20 experimental methods, and 4302 subject descri ptors. On average, each term had about 90 weighted neighboring terms i ndicating relevant concepts. The thesaurus was developed as an online search aide. We tested the worm thesaurus in an experiment with six wo rm researchers of varying degrees of expertise and background. The exp eriment showed that the thesaurus was an excellent ''memory-jogging'' device and that it supported learning and serendipitous browsing. Desp ite some occurrences of obvious noise, the system was useful in sugges ting relevant concepts for the researchers' queries and it helped impr ove concept recall. With a simple browsing interface, an automatic the saurus can become a useful tool for online search and can assist resea rchers in exploring. and traversing a dynamic and complex electronic c ommunity system.