Current search paradigms for the Web, direct access through search engines and
navigational access via static taxonomies, have recently been strongly criticized.
A third paradigm, dynamic taxonomies or faceted search, is gaining acceptance to
the extent that it is now the de facto standard in product selection for e-commerce.
This new paradigm is based on a simple and easily understood visual environment
which supports both direct access and guided exploration of complex information
bases. While focusing on structured, guided exploration, it also bridges the
gap between traditional querying and browsing. In general, query services are either
too simplistic (e.g. free text queries in IR systems or Web search engines), or
too complex for casual users (e.g. SQL queries, or Semantic Web queries). Browsing
as well, is either too simplistic (e.g. “plain” Web links) or application specific
(dynamic pages derived by specific application programs), and does not support
conceptual exploration.
Dynamic taxonomies work on multidimensional taxonomies (usually organized
by facets) and provide a single, coherent visual framework in which users can focus
on one or more concepts in the taxonomy, and immediately see a conceptual summary
of their focus, in the form of a reduced taxonomy derived from the original
one by pruning unrelated concepts. Concepts in the reduced taxonomy can be used
to set additional, dependent foci and users iterate in a guided yet unconstrained way
until they reach a result set sufficiently small for manual inspection.
The access paradigm supported is a conceptual exploration, far more frequent in
“search” tasks than the retrieval by exact specification supported by search engines
and database queries. The underlying model is simple and easily understood by
users, offers substantial benefits over traditional approaches, and has an extremely
wide application range, and a potential for important extensions. Dynamic taxonomy/
faceted search is a heavily interdisciplinary area, where data modeling, human
factors, logic, inference, and efficient implementations must be considered holistically.