Deductive Planning and Pathfinding for Relational Data Bases
Inference planning techniques have been implemented and incorporated within a prototype deductive processor designed to support the extraction of information implied by, but not explicitly included in, the contents of a relationally structured data base, Deductive pathfinding and inference planning are used to select small sets of relevant premises and to construct skeletal derivations. When these “skeletons” are verified, the system uses them as plans to create data-base access strategies that guide the retrieval of data values, to assemble answers to user requests, and to produce proofs supporting those answers. Several examples are presented to illustrate the current capability of the prototype Deductively Augmented Data Management (DADM) system.
KeywordsSemantic Network Conjunctive Normal Form Inference Plan Search Request Control Processor
Unable to display preview. Download preview PDF.
- 1.Davis, R. and King, J.  An Overview of Production Systems, AIM-271, Artificial Intelligence Laboratory, Stanford University, 1975.Google Scholar
- 2.Elliott, R. W.  A Model for a Fact Retrieval System, TNN-42, Computation Center, University of Texas, Austin, 1965.Google Scholar
- 3.Kellogg, C. H., Burger, J., Diller, T. and Fogt, K.  The CONVERSE Natural Language Data Management System: Current Status and Plans, Proceedings Symposium on Information Storage and Retrieval, ACM, New York, 1971, 33–46.Google Scholar
- 4.Kellogg, C., Klahr, P. and Travis, L.  A Deductive Capability for Data Management, In Systems for Large Data Bases (P.C. Lockemann and E. J. Neuhold, Eds.), North Holland, Amsterdam, 1976, 181–196.Google Scholar
- 5.Kellogg, C., Klahr, P. and Travis, L.  Deductive Methods for Large Data Bases, Fifth International Joint Conference on Artificial Intelligence, MIT, Cambridge, Mass., 1977, 203–209.Google Scholar
- 6.Klahr, P.  “The Deductive Pathfinder: Creating Derivation’ Plans for Inferential Question-Answering,” Ph.D. Dissertation, Computer Science Dept., University of Wisconsin, Madison, Wisconsin, 1975.Google Scholar
- 7.Klahr, P.  Planning Techniques for Rule Selection in Deductive Question-Answering, In Pattern-Directed Inference Systems (D. Waterman and F. Hayes-Roth, Eds.), Adademic Press, New York, 1978.Google Scholar
- 9.McSkimin, J. and Minker, J.  A Predicate Calculus Based Semantic Network for Question-Answering Systems, In Associative Networks — The Representation and Use of Knowledge in Computers (N. Findler, Ed.), Academic Press, New York, 1978.Google Scholar
- 10.McSkimin, J. and Minker J.  The Use of a Semantic Network in a Deduction Question-Answering System, Fifth International Joint Conference on Artificial Intelligence, MIT, Cambridge, Mass., 1977, 50–58.Google Scholar
- 11.Reiter, R.  Deductive Question-Answering in Relational Data Bases, In Logic and Data Bases (H. Gallaire and J. Minker, Eds.), Plenum Press, New York, New York, 1978, 149–177.Google Scholar
- 14.Travis, L., Kellogg, C. and Klahr, P.  Inferential Question-Answering: Extending CONVERSE, SP-3679, System Development Corporation, Santa Monica, Calif., 1973.Google Scholar