Matchmaking for information agents

  • Authors:
  • Daniel Kuokka;Larry Harada

  • Affiliations:
  • Lockheed Palo Alto Research Labs, Palo Alto, CA;Lockheed Palo Alto Research Labs, Palo Alto, CA

  • Venue:
  • IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 1995

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Abstract

Factors such as the massive increase in information available via electronic networks and the advent of virtual distributed workgroups for commerce are placing severe burdens on traditional methods of information sharing and retrieval. Matchmaking proposes an intelligent facilitation agent that accepts machine-readable requests and advertisements from information consumers and providers, and determines potential information sharing paths. We argue that matchmaking permits large numbers of dynamic consumers and providers, operating on rapidly-changing data, to share information more effectively than via current methods. This paper introduces matchmaking, as enabled by knowledge sharing standards like KQML, and describes the SHADE and COINS matchmaker implementations. The utility and initial results of matchmaking are illustrated via example scenarios in engineering and consumer information retrieval.