Intelligent query answering by knowledge discovery techniques

Jiawei Han, Yue Huang, Nick Cercone, Yongjian Fu

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)373-390
Number of pages18
JournalIEEE Transactions on Knowledge and Data Engineering
Volume8
Issue number3
DOIs
StatePublished - 1996
Externally publishedYes

Keywords

  • Database and knowledge-base systems
  • Intelligent query answering
  • Knowledge discovery in databases
  • Knowledge-rich data model
  • Multiple layered databases
  • Query analysis and query processing

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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