Intelligent query answering in rule based systems
Journal of Logic Programming
On conjunctive queries containing inequalities
Journal of the ACM (JACM)
Foundations of semantic query optimization for deductive databases
Foundations of deductive databases and logic programming
Using integrity constraints to provide intensional answers to relational queries
VLDB '89 Proceedings of the 15th international conference on Very large data bases
Logic and Databases: A Deductive Approach
ACM Computing Surveys (CSUR)
A completeness theorem and a computer program for finding theorems derivable from given axioms
A completeness theorem and a computer program for finding theorems derivable from given axioms
Intelligent query answering in deductive and object-oriented databases
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Intensional query processing using data mining approaches
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Domain Analysis and Queries in Context
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
| Hi-index | 0.01 |
Intensional answers are conditions that tuples of values must satisfy to belong to the usual extensional answer of a query addressed to a deductive database. The authors review the concept of intensional answers and introduce a general method for generating them as logical consequences of the query and of deduction rules. The authors show how integrity constraints can filter out inadequate answers and produce simpler and more informative answers. An efficient organization for the combination of answers and constraints is described. The introduction of negation in queries and in the body of deduction rules is discussed. Beyond the mechanics of answer generation, the interest of the approach also depends on a strategy for selecting answers to a user submitting a query. This requires techniques for user modeling and dialogue management similar to those required for expert systems.