An Associative Model of Word Selection in the Generation of Search Queries
To generate a search query based on an end-user request, a database searcher has to select appropriate search terms. These terms can either be taken from the request, or they can be added by the searcher. This selection process is simulated by an associative lexical net; the nodes of the net are the terms used in 94 records of written requests to a psychological information agency and the respective on-line searches. The weights connecting the nodes are calculated from the co-occurrences of these terms in the abstracts of the database PsycLIT. To simulate the term selection process for a query, the nodes of all terms used in the written request are activated, and one or more spreading activation cycles are performed. The result of the simulation is a ranking of the terms according to the activities of their nodes. Simulations for all 94 records show a low mean activity rank for the terms selected from the request; the mean activity rank for new terms added by the searcher is lower than the mean activity rank for those terms of the request that were not used in the query.

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