title: User-controlled mapping of significant literatures.
abstract: We apply a version of our web-based literature-mapping system to PNAS for 1971-2002, as indexed by the National Library of Medicine and the Institute for Scientific Information. Given a single input term from a user, a medical subject heading, a cocited author, or a cocited journal, PNASLINK rapidly displays views in which that term and the other 24 terms that most frequently co-occur with it in a bibliographic database are interrelated in ways suggesting fruitful combinations for document retrieval. The interrelationships are produced by two algorithms, pathfinder networks and Kohonen-style self-organizing maps. PNASLINK displays are themselves interactive interfaces that can retrieve documents from digital libraries (e.g., PNAS Online). This style of visualizing knowledge domains is called "localized" because it does not attempt to map the indexing of literatures in full but concentrates on the top terms in an "associative thesaurus" reflecting user interests. It also permits swift remappings, as the user recognizes terms worth pursuing. PNASLINK is illustrated with maps drawn from the literature of population genetics. Some comparative and evaluative comments are added, one from a domain expert indicating that the face validity of the system may be tempered by insufficient specificity in the indexing terms being mapped.
authors.affiliation: College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA. whitehd@drexel.edu
authors.forename: Howard D
authors.initials: HD
authors.lastname: White
authors.forename: Xia
authors.initials: X
authors.lastname: Lin
authors.forename: Jan W
authors.initials: JW
authors.lastname: Buzydlowski
authors.forename: Chaomei
authors.initials: C
authors.lastname: Chen
mesh_terms: D016206:Databases, Bibliographic / Q000639:trends*; D005787:Gene Frequency; D005828:Genetics, Population; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D009307:National Academy of Sciences, U.S.; D016571:Neural Networks, Computer; D009862:Online Systems; D010506:Periodicals as Topic; D014481:United States