Intelligent query answering by knowledge discovery techniques

51Citations
Citations of this article
25Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Knowledge discovery facilitates querying database knowledge and intelligent query answering in database systems. In this paper, we investigate the application of discovered knowledge, concept hierarchies, and knowledge discovery tools for intelligent query answering in database systems. A knowledge-rich data model is constructed to incorporate discovered knowledge and knowledge discovery tools. Queries are classified into data queries and knowledge queries. Both types of queries can be answered directly by simple retrieval or intelligently by analyzing the intent of query and providing generalized, neighborhood or associated information using stored or discovered knowledge. Techniques have been developed for intelligent query answering using discovered knowledge and/or knowledge discovery tools, which includes generalization, data summarization, concept clustering, rule discovery, query rewriting, deduction, lazy evaluation, application of multiple-layered databases, etc. Our study shows that knowledge discovery substantially broadens the spectrum of intelligent query answering and may have deep implications on query answering in data- and knowledge-base systems. ©1996 IEEE.

Cite

CITATION STYLE

APA

Han, J., Huang, Y., Cercone, N., & Fu, Y. (1996). Intelligent query answering by knowledge discovery techniques. IEEE Transactions on Knowledge and Data Engineering, 8(3), 373–390. https://doi.org/10.1109/69.506706

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free