Artificial Intelligence Lab, Department of MIS, University of Arizona / This paper presents a framework for knowledge discovery
and concept exploration. In order to enhance the concept
exploration capability of knowledge-based systems and to
alleviate the limitations of the manual browsing approach,
we have developed two spreading activation-based algorithms
for concept exploration in large, heterogeneous networks
of concepts (e.g., multiple thesauri). One algorithm,
which is based on the symbolic Al paradigm, performs a
conventional branch-and-bound search on a semantic net
representation to identify other highly relevant concepts
(a serial, optimal search process). The second algorithm,
which is based on the neural network approach, executes
the Hopfield net parallel relaxation and convergence process
to identify â convergentâ concepts for some initial
queries (a parallel, heuristic search process). Both algorithms
can be adopted for automatic, multiple-thesauri
consultation. We tested these two algorithms on a large
text-based knowledge network of about 13,000 nodes
(terms) and 80,000 directed links in the area of computing
technologies. This knowledge network was created from
two external thesauri and one automatically generated
thesaurus. We conducted experiments to compare the behaviors
and performances of the two algorithms with the
hypertext-like browsing process. Our experiment revealed
that manual browsing achieved higher-term recall but
lower-term precision in comparison to the algorithmic systems.
However, it was also a much more laborious and cognitively
demanding process. In document retrieval, there
were no statistically significant differences in document recall
and precision between the algorithms and the manual
browsing process. In light of the effort required by the manual
browsing process, our proposed algorithmic approach
presents a viable option for efficiently traversing largescale,
multiple thesauri (knowledge network).
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105241 |
| Date | 06 1900 |
| Creators | Chen, Hsinchun, Ng, Tobun Dorbin |
| Publisher | Wiley Periodicals, Inc |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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