Algorithmic approach to building concept space for a scientific community

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This research reports an algorithmic approach to the generation of an organizational (community) memory for a scientific community. The techniques used included object filtering, automatic indexing, and cluster analysis. The testbed for our research was the Worm Community System, which contained various forms of (C. elegans) worm-related knowledge and literature, currently in use by molecular biologists in the C. elegans-related research community. The resulting organizational memory was represented as a knowledge base (or frame-based thesaurus). It included 2,709 researchers' names, 798 gene names, 20 experimental methods, and 4,302 subject descriptors.

Original languageEnglish (US)
Title of host publicationProceedings of the Hawaii International Conference on System Sciences
EditorsJay F. Nunamaker, Ralph H.Jr. Sprague
PublisherPubl by IEEE
Pages201-210
Number of pages10
ISBN (Print)081865080X
StatePublished - Jan 1 1994
EventProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5) - Wailea, HI, USA
Duration: Jan 4 1994Jan 7 1994

Publication series

NameProceedings of the Hawaii International Conference on System Sciences
Volume4
ISSN (Print)1060-3425

Other

OtherProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5)
CityWailea, HI, USA
Period1/4/941/7/94

ASJC Scopus subject areas

  • Computer Science(all)

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  • Cite this

    Chen, H. (1994). Algorithmic approach to building concept space for a scientific community. In J. F. Nunamaker, & R. H. J. Sprague (Eds.), Proceedings of the Hawaii International Conference on System Sciences (pp. 201-210). (Proceedings of the Hawaii International Conference on System Sciences; Vol. 4). Publ by IEEE.