TY - GEN
T1 - Using domain knowledge in knowledge discovery
AU - Yoon, Suk Chung
AU - Henschen, Lawrence J.
AU - Park, E. K.
AU - Makki, Sam
PY - 1999
Y1 - 1999
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0033279048&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0033279048&partnerID=8YFLogxK
U2 - 10.1145/319950.320008
DO - 10.1145/319950.320008
M3 - Conference contribution
AN - SCOPUS:0033279048
SN - 1581131461
SN - 9781581131468
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 243
EP - 250
BT - International Conference on Information and Knowledge Management, Proceedings
PB - ACM
T2 - Proceedings of the 1999 8th International Conference on Information Knowledge Management (CIKM'99)
Y2 - 2 November 1999 through 6 November 1999
ER -