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Link to original content: https://doi.org/10.1023/A:1008389615976
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Constructing Information Bases Using Associative Structures

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Abstract

We present an approach based on knowledge medium using associative structures as a framework of information representation to gather raw information from heterogeneous information sources and to integrate it into information bases cost-effectively.

We then present a knowledge media information base system called CM-2 which provides users with a means of accumulating, sharing, exploring and refining conceptually diverse information gathered from vast information sources. We describe the system's four major facilities; (a) an information capture facility, (b) an information integration facility, (c) an information retrieval facility and (d) an information refinement facility. We discuss the strength and weakness of our approach by analyzing results of experiments.

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References

  1. Mark Stefik, “The next knowledge medium,” AI Magazine, vol. 7,no. 1, pp. 34–46, 1986.

    Google Scholar 

  2. Eric Brill, “Some advance in transformation-based part of speech tagging,” in Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 1994.

  3. M.R. Quillian, “Semantic memory,” in Marvin Minsky edition, Semantic Information Processing, MIT Press, 1968.

  4. Toyoaki Nishida and Hideaki Takeda, “Towards the knowledgeable community,” in Proceedings of International Conference on Building and Sharing of Very Large-Scale Knowledge Bases 93, Japan Information Processing Development Center, 1993, pp. 157–166.

  5. Alon Y. Levy, Yehoshua Sagiv, and Divesh Srivastava, “Towards efficient information gathering agents,” in Working Notes of the AAAI Spring Symposium on Software Agents, 1994, pp. 64–70.

  6. Robert Armstrong, Dayne Freitag, Thorsten Joachims, and Tom Mitchell, “A learning apprentice for the World Wide Web,” in Working Notes of the AAAI Spring Symposium on Information Gathering from Heterogeneous Distributed Environments, 1995, pp. 6–12.

  7. Marko Balabanovi'c and Yoav Shoham, “Learning information retrieval agents: Experiments with automated web browsing,” in Working Notes of the AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, 1995, pp. 13–18.

  8. Wen-Syan Li, “Knowledge gathering and matching in heterogeneous databases,” in Working Notes of the AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, 1995, pp. 116–121.

  9. R.V. Guha and D.B. Lenat, “Enabling agents to work together,” in Communications of ACM, vol. 37,no. 7, 1994, pp. 127–142.

    Google Scholar 

  10. R.S. Patil et al., “The DARPA knowledge sharing effort: Progress report. Principles of knowledge representation and reasoning,” in Proceedings of the Third International Conference, edited by C. Rich, B. Nebel, and W. Swartout, Morgan Kaufmann, 1992.

  11. B.R. Gaines and M.L.G. Shaw, “Using knowledge acquisition and representation tools to support scientific communities,” in AAAI-94, 1994.

  12. R. Grishman and B. Sundheim, “Message understanding conference-6: A brief history,” in Proceedings of The 16th International Conference on Computational Linguistics (COLING-96), 1996, pp. 466–471.

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Maeda, H., Koujitani, K. & Nishida, T. Constructing Information Bases Using Associative Structures. Applied Intelligence 10, 85–99 (1999). https://doi.org/10.1023/A:1008389615976

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