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Summary:As part of the knowledge engineering activities for building a computerized intermediary search system, an empirical study was conducted to gain insights into the performance of an expert human intermediary. Based on her interactions with 17 information seekers, a model was developed that describes certain ways in which she used subject-specific knowledge to help them refine their topics. In this model, suggestions for topic refinement are generated by applying certain knowledge-based search tactics to a specific type of knowledge-structure (frames). The intermediary's performance during the 17 search sessions can be described as including 328 applications of such tactics. The insights gained from these results have potentially important implications for the design of computerized intermediary systems, as well as for the training of human intermediaries.
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ISSN:0306-4573
1873-5371
DOI:10.1016/0306-4573(93)90021-5