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Introduction
Web Conceptual Space
Robert E. Kent
School of EECS
Washington State University
USA
rekent@eecs.wsu.edu
Christian Neuss
Fachgebiet Praktische Informatik
Technische Hochschule Darmstadt
Germany
neuss@isa.informatik.th-darmstadt.de
Abstract: In this paper various tools and techniques from the mathematical theory of conceptual
knowledge processing [Wille 1982] [Wille 1992] are applied to the conceptual universe of the
World Wide Web. For the efficient and economical management of conceptual knowledge, the new
idea of conceptual space is introduced. For the conceptual empowerment of the Web user, a new
technique called conceptual browsing [Kent & Neuss 1996a] is advocated. Conceptual browsing,
which browses over conceptual space along conceptual links, is dual mode (extentional versus
intentional) and dual scope (global versus local).
Discovery of relevant resources is still one of the biggest problem in the continuously growing infrastructure of the
World Wide Web. In order to allow the Web to become a true electronic library, it needs a service that identifies and
locates documents belonging to a given category, based on descriptive document attributes such as author, title, or
subject. In traditional library science, resources are identified through catalog information, which is organized as a
hierarchy of restricted subject categories. Searches are conducted upon this explicitly encoded descriptive information,
and can easily be supported with relatively simple retrieval programs. Although traditional library science maintains
indexes manually, the dynamic nature of electronic documents requires a certain automation of this task. Not only
does the pure vastness of the document space forbid manual indexing, but many of the electronic documents are also
subject to frequent change. Currently, the popular searchable indexes of World Wide Web resource information are
based upon Web robots: programs that connect to a remote site and recursively retrieve documents over the Network,
usually in order to build an index. Since the HTML markup language provides relatively little support for encoding
document structure and semantic information [Nicol 1995], automatic tools have to search the document text and
employ heuristic methods in order to judge document relevance.
In order to address this problem, recent research aims at providing self-identifying document structure [Barnard et al.
1995], standards for the representation of metadata [Weibel et al. 1995] [Bowman & Schwartz 1996], and scaleable,
distributed directory services for locating information resources such as Harvest [Bowman et al. 1994a] or the
Synopsis File System [Bowman 1996]. Provided that sufficient descriptive information about documents is available
for resource discovery tools, the question arises how the information acquired can best be digested and manipulated.
One approach is to employ a graphical metaphor to represent information structures, and provide users with a maplike
view of the underlying information space [Robertson 1993]. These information visualization techniques can
successfully be applied to the World Wide Web [Mukherja & Foley 1995]. However, creation of an effective view is
difficult, as the available descriptive information lacks many useful semantic attributes [ibid.]. In general, visualization
involves a two- or three-dimensional projection from a multidimensional attribute space, and thus requires an
interpretation of the raw attribute data.