Human-agent service matching using natural language queries: system test and training
article
Smart environments, ambient intelligence and intelligent agents leave the user lost between large amounts of services. Ad-hoc networks, mobile agents and mobile devices make the set of available services dynamic over time and space, increasing the users problems to find the service he needs. Earlier, we presented a ServiceMatcher that can find the agent best fitting to the users natural language request. This paper presents performance results of the ServiceMatcher. The test queries come from human users in a realistic scenario (see our other paper in this issue). With a short training of the agent vocabularies, over 80% correct service matches are found.
Topics
TNO Identifier
16412
Source
Personal and Ubiquitous Computing., 10(6), pp. 393-399.
Pages
393-399
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