VISAR: a system for inference and navigation of hypertext

ABSTRACT

Hypertext systems have traditionally been constructed by hand. This process can stand improvement in several aspects: it is laborious; requires a human to understand the text and infer all the relationships between the concepts/topics; and while the resulting hypertext may be traversed by a reader in an arbitrary fashion, s/he may still find it difficult to understand the concepts as expressed by the builder of the hypertext. We present a knowledge-intensive assistant for building hypertext fragments from a knowledge base customised both explicitly and implicitly by a user. Such a presentation may clarify relationships between concepts that were present implicitly in multiple sources of information. In the domain of an intelligent information retrieval system, we show how such an assistant may render customised views of knowledge extracted in a manageable form. While the presentation medium of the original system is graphic, we also speculate that presentation of the information in alternative hypermedia appears to be straightforward.

REFERENCES

• 1: Wiliam O. Beeman , Kenneth T. Anderson , Gail Bader , James Larkin , Anne P. McClard , Patrick McQuillan , Mark Shields, Hypertext and pluralism: from lineal to non-lineal thinking, Proceeding of the ACM conference on Hypertext, p.67-88, November 1987, Chapel Hill, North Carolina, United States [doi>10.1145/317426.317434]
• 2: Clitherow, P.A,, et al, VISAR: An Intelligent Interface Agent for Information Retrieval, in preparation, July 1989~
• 3: Paul R. Cohen , Rick Kjeldsen, Information retrieval by constrained spreading activation in semantic networks, Information Processing and Management: an International Journal, v.23 n.4, p.255-268, July 1987 [doi>10.1016/0306-4573(87)90017-3]
• 4: George H. Collier, Thoth-II: hypertext with explicit semantics, Proceeding of the ACM conference on Hypertext, p.269-289, November 1987, Chapel Hill, North Carolina, United States [doi>10.1145/317426.317446]
• 5: W. Bruce Croft, Approaches to intelligent information retrieval, Information Processing and Management: an International Journal, v.23 n.4, p.249-254, July 1987 [doi>10.1016/0306-4573(87)90016-1]
• 6: S. T. Dumais , G. W. Furnas , T. K. Landauer , S. Deerwester , R. Harshman, Using latent semantic analysis to improve access to textual information, Proceedings of the SIGCHI conference on Human factors in computing systems, p.281-285, May 15-19, 1988, Washington, D.C., United States [doi>10.1145/57167.57214]
• 7: Egan, D. "Superbook: Behavioral evaluation and analysis", In Proc. Bellcore End User Computing Symposium 1989, Piscataway NJ: 13ellcore, in press.
• 8: Egido, C., Bussey, H., Kaplan, A., and Rohall, S., "PIGS: A passive information grazing system", Poster presented at SIGCI-I/'89, Austin TX.
• 9: Fairchild, K.M., Poltrock, S.E., Furnas, G.W., "SemNet: Three-Dimensional Graphic Representations of Large Knowledge Bases", in Cognitive Science and its Applications for Human-Computer Interaction, Guindon, R. (Ed), Lawrence Erlbaum, Hillsdale, NJ, 1988.
• 10: Edward A. Fox, Development of the CODER system: a testbed for artificial intelligence methods in information retrieval, Information Processing and Management: an International Journal, v.23 n.4, p.341-366, July 1987 [doi>10.1016/0306-4573(87)90022-7]
• 11: Frank G. Halasz, Reflections on NoteCards: seven issues for the next generation of hypermedia systems, Proceeding of the ACM conference on Hypertext, p.345-365, November 1987, Chapel Hill, North Carolina, United States [doi>10.1145/317426.317451]
• 12: Lenat, D.B., et al, "Knoesphere: Building Expert Systems with Encylopedic Knowledge", in Proceedings oflJCAI-83, Karlsrue, b"RG, 1983.
• 13: Doug Lenat , Mayank Prakash , Mary Shepherd, CYC: Using common sense knowledge to overcome brittleness and knowledge acquistion bottlenecks, AI Magazine, v.6 n.4, p.65-85, Winter 1986
• 14: Lenat, D.B., Guha, R.V., The World According to CYC, MCC Tech Report, ACA-AI-300-88, September 1988.
• 15: Miller, G.A., "The magical number seven, plus or minus two: Some limits on our capacity for processing information", Psychological Review, 63, pp. 81-97, 1956.
• 16: Nilson, M.E., "A Knowledge-Based Approach to information Filtering", IEEE International Workshop on Telematics, Denver, CO 1989.
• 17: Rich, E., "Users are individuals", lntl. Journal of Man-Machine Studies, 18, 1983.
• 18: Steven Pollitt, CANSEARCH: An expert systems approach to document retrieval, Information Processing and Management: an International Journal, v.23 n.2, p.119-138, March 1987 [doi>10.1016/0306-4573(87)90053-7]
• 19: Lisa F. Rau, Knowledge organization and access in a conceptual information system, Information Processing and Management: an International Journal, v.23 n.4, p.269-283, July 1987 [doi>10.1016/0306-4573(87)90018-5]
• 20: Gerard Salton, Another look at automatic text-retrieval systems, Communications of the ACM, v.29 n.7, p.648-656, July 1986 [doi>10.1145/6138.6149]
• 21: Gerald Salton, Automatic text indexing using complex identifiers, Proceedings of the ACM conference on Document processing systems, p.135-144, December 05-08, 1988, Santa Fe, New Mexico, United States [doi>10.1145/62506.62530]
• 22: Schatz, B., "Telesophy: System support for the abstract model of an information space", in Proceedings of Bellcore End User Computing Symposium, Bellcore, Piscataway NJ, November 1988, in press.
• 23: Stephen J. Wiesner, Two-&-Two, a high level system for retrieving pairs of documents, ACM SIGOIS Bulletin, v.9 n.4, p.1-4, Oct. 1988 [doi>10.1145/51640.51641]
• 24: Wittenburg, K., Natural Language Parsing with Combinatory Cetegorical Grammars in a Graph-Unification-Based Formalism, Ph.D. thesis, University of Texas, Austin, TX, 1986.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

General Terms:
Design