Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1145/319950.320008 | CIKM |
Keywords | Field | DocType |
significant cost reduction,exhaustive search,query optimization,knowledge discovery,relevant domain knowledge,knowledge discovery process,equivalent query,semantic query optimization,relevant portion,domain knowledge,knowledge discovery applications deal,summarization,classification,digital libraries,aggregation,computational complexity | Query optimization,Web search query,Data mining,Automatic summarization,Brute-force search,Domain knowledge,Information retrieval,Computer science,Knowledge-based systems,Knowledge extraction,Software mining | Conference |
ISSN | ISBN | Citations |
Knowledge-Based Systems | 1-58113-146-1 | 16 |
PageRank | References | Authors |
0.98 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Suk-Chung Yoon | 1 | 40 | 5.55 |
| Lawrence J. Henschen | 2 | 478 | 280.94 |
| E. K. Park | 3 | 20 | 1.51 |
| Sam Makki | 4 | 18 | 2.50 |