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A multi-agent based knowledge search framework to support the product development process

By Guo Jian, James Gao and Yinglin Wang


The amount of information available via networks and databases highlights the limited assistance of existing search and retrieval engines in locating relevant information. Owing to the rising demand for information retrieval, manufacturers employ various search techniques to provide a more satisfied information retrieval performance in its domain. As a knowledge-intensive activity, a product development team seeks a more effective knowledge search to achieve competitive advantage. This paper proposes a knowledge search methodology using autonomous, intelligent agents to transform passive search and retrieval engines into active, personal assistants for the product development process. The combination of effective information retrieval techniques and autonomous, intelligent agents will improve the performance of short-term information retrieval in existing search or retrieval engines. Results of the research project will be presented and discussed. This includes a multi-agent approach for knowledge search, the selection of agent construction tools, and the current implementation of the proposed methodology

Topics: Q1, TS
Publisher: Taylor & Francis
Year: 2010
DOI identifier: 10.1080/09511920903529222
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