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The reordering of rectangular hypertext matrices can be extremely
useful in the development of visual browsers for finding
related information. Such tools can aid users in locating
documents relevant to specific queries in an immediate fashion
(i.e., by clusters of hypertext). From Figure 4,
for example, we can extract the cluster of articles (see
Figure 6)
from the letter A of Condensed Columbia Encyclopedia related to
people and regions of Persia around 300 BC. Notice that in graph
depicted in Figure 6 there are several related
articles (shown in blue) not in the collection (i.e., 850 letter A
articles) which are links contained in
different but related letter A articles:
Demosthenes, Diadochi, Greece, Macedon,
Peloponnesus, Persia, and Phillip II. This
cluster of related hypertext information is fully contained
within a subwindow of each of reorderings for the 1778 links
by 850 articles CCE-A matrix shown in Figure 7.
The display of graphs such as that in Figure 6 coupled
with windowing capabilities (e.g., mouse dragging) in a visualization
tool for hypertext browsing would be highly effective for scoping the
context of large and possibly distributed databases.
Figure 6: Graph of Persia-related articles from CCE-A for
browsing.
Figure 7: Partitioned windows containing graph of Persia-related
CCE-A articles.
If the entire collection of articles (letters A through Z) of the
Condensed Columbia Encyclopedia were distributed across a network
(local or even the World-Wide-Web), the graph in Figure 6
as traced by the windows in Figure 7 would allow a user
to selectively retrieve foreign or remote documents (e.g., articles
from letters B through Z) linked to relevant local documents (e.g.,
articles from letter A). The relationship of remote documents
with both local and other remote documents would be immediately
determined by providing a road map of related information across
the network. Without such hypertext clustering, related local documents
such as Achaea and Arcadia from Figure 6 might
be difficult to associate without knowing their common linkage to
remote documents such as
Peloponnesus and Greece a priori. That is, there would be
no need to retrieve the actual texts of Achaea and Arcadia
(or their links) to discover their similarity.
Next: Summary and Future
Up: Performance on Hypertext
Previous: Computational Time
Michael W. Berry (berry@cs.utk.edu)
Mon Jan 29 14:30:24 EST 1996