Foundations of logic programming
Foundations of logic programming
Semantic query optimization in expert systems and database systems
Proceedings from the first international workshop on Expert database systems
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Logic-based approach to semantic query optimization
ACM Transactions on Database Systems (TODS)
Readings in object-oriented database systems
Readings in object-oriented database systems
Database systems: achievements and opportunities
Communications of the ACM
Introduction to object-oriented databases
Introduction to object-oriented databases
Building an object-oriented database system: the story of 02
Building an object-oriented database system: the story of 02
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A classification algorithm for supporting object-oriented views
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Intelligent query answering in deductive and object-oriented databases
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Semantic query processing in object-oriented databases using deductive approach
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Advances in knowledge discovery and data mining
Logic and Databases: A Deductive Approach
ACM Computing Surveys (CSUR)
Query Processing for Advanced Database Systems
Query Processing for Advanced Database Systems
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Abstract-Driven Pattern Discovery in Databases
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
The Role of Domain Knowledge in a Large Scale Data Mining Project
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
SoPhIA: a unified architecture for knowledge discovery
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
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With the explosive growth of the size of databases, many knowledge discovery applications deal with large quantities of data. There is an urgent need to develop methodologies which will allow the applications to focus search to a potentially interesting and relevant portion of the data, which can reduce the computational complexity of the knowledge discovery process and improve the interestingness of discovered knowledge. Previous work on semantic query optimization, which is an approach to take advantage of domain knowledge for query optimization, has demonstrated that significant cost reduction can be achieved by reformulating a query into a less expensive yet equivalent query which produces the same answer as the original one. In this paper, we introduce a method to utilize three types of domain knowledge in reducing the cost of finding a potentially interesting and relevant portion of the data while improving the quality of discovered knowledge. In addition, we propose a method to select relevant domain knowledge without an exhaustive search of all domain knowledge. The contribution of this paper is that we lay out a general framework for using domain knowledge in the knowledge discovery process effectively by providing guidelines.