Artificial Intelligence Lab, Department of MIS, University of Arizona / This article presents research on the design of knowledge-based document retrieval systems. We adopted a semantic network structure to represent subject knowledge and classification scheme knowledge and modeled experts' search strategies and user modeling capability as procedural knowledge. These functionalities were incorporated into a prototype knowledge-based retrieval system, Metacat. Our system, the design of which was based on the blackboard architecture, was able to create a user profile, identify task requirements, suggest heuristics-based search strategies, perform semantic-based search assistance, and assist online query refinement.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105775 |
| Date | 06 1900 |
| Creators | Chen, Hsinchun |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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