This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Making the Knowledge Base Systems More Efficient: A Method to Detect Inconsistent Queries
August 1994 (vol. 6 no. 4)
pp. 634-639

The processing cost of queries with an empty answer, both in the database and knowledge base context, is usually high. One purpose of semantic query optimization methods in the database context is to use semantic knowledge to detect such types of queries. Although semantic query optimization is well known in the database context, this is not the case for knowledge base systems (KBSs). This paper presents a method that allows the detection of queries with an empty answer using only semantic information expressed in the knowledge base definition. The method can be applied in the context of KBSs that provide some of the following features: structuring mechanisms, assertional knowledge, temporal information, and handling of inequality expressions.

[1] U.S. Chakravarthy, J. Grant, and J. Minker, "Logic-based approach to semantic query optimization,"ACM Trans. Database Syst., vol. 15, pp. 162-207, 1990.
[2] M. Jarke, "External semantic query simplification: A graph-theoretic approach and its implementation in Prolog," inProc. 1st Int. Conf. Expert Database Syst., Kiawah, Isl., SC, Oct. 1984, pp. 467-482.
[3] S. T. Shenoy and Z. M. Ozsoyoglu, "A system for semantic query optimization," inProc. ACM SIGMOD, May 1987, pp. 181-195.
[4] M. Hammer and S. Zdonik, "Knowledge based query processing," inProc.6th VLDB Conf., 1980, pp. 137-147.
[5] J.J. King, "Query optimization by semantic reasoning," Ph.D. dissertation, Stanford Univ., May 1981. Also published by University of Michigan Press, 1984.
[6] S. Shekhar, J. Srivastava, and S. Dutta, "A formal model of trade-off be tween optimization and execution costs in semantic query optimization," inData&Knowl. Eng., vol. 8, no. 2, pp. 131-151, 1992.
[7] C. Peltason, A. Schmiedel, C. Kindermann, and J. Quantz, "The BACK system revised," Tech. Univ. Berlin, Germany, Sept. 1989.
[8] M. Jarke and M. Koubarakis, "Query optimization in KBMS: Overview, research issues. and concepts for a Telos implementation," Tech. Rep. KRR-TR-89-6, Dept. of Comput. Sci., Univ. of Toronto, ON, Canada, 1989.
[9] F. Bry, H. Decker, and R. Manthey, "A uniform approach to constraint satisfaction and constraint satisfiability in deductive databases," inProc. Conf. Extending Data Base Technology, Venice, Springer-Verlag, 1988.
[10] J. D. Ullman,Database and Knowledge-base Systems. Rockville, MD: Computer Science Press, 1988.
[11] M. E. Stickel, "Automated deduction by theory resolution," inProc. IJCAI-85 Conf., 1985, pp. 455-458.
[12] C. L. Chang and R. C. T. Lee,Symbolic Logic and Mechanical Theorem Proving. New York: Academic, 1973.
[13] D. J. Rosenkrantz and M. H. Hunt, "Processing conjunctive predicates and queries," inProc. Conf. on Very Large Databases, 1988, pp. 318-330.
[14] X. Sun, N. Kamel, and L. M. Ni, "Solving implication problems in database applications," inProc. ACM SIGMOD, May 1989, pp. 185- 192.

Index Terms:
query processing; knowledge based systems; database management systems; optimisation; knowledge base systems; inconsistent query detection; empty answer; database; semantic query optimization methods; semantic knowledge; semantic query optimization; semantic information; knowledge base definition; structuring mechanisms; assertional knowledge; temporal information; inequality expressions
Citation:
A. Illarramendi, J.M. Blanco, A. Goñi, "Making the Knowledge Base Systems More Efficient: A Method to Detect Inconsistent Queries," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 4, pp. 634-639, Aug. 1994, doi:10.1109/69.298179
Usage of this product signifies your acceptance of the Terms of Use.