Intelligent Query Answering by Knowledge Discovery Techniques

نویسندگان

  • Jiawei Han
  • Yue Huang
  • Nick Cercone
  • Yongjian Fu
چکیده

Knowledge discovery in databases facilitates querying database knowledge, cooperative query answering and semantic query optimization 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 classiied 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 deduction, generalization , data summarization, concept clustering, rule discovery, query rewriting, lazy evaluation, semantic query optimization, etc. Our study shows that knowledge discovery substantially broadens the spectrum of intelligent query answering and may have deep implications on query processing in data-and knowledge-base systems. Index Terms { Database and knowledge-base systems, knowledge discovery in databases, knowledge-rich data model, intelligent query answering, semantic query optimization, query analysis and query processing.

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عنوان ژورنال:
  • IEEE Trans. Knowl. Data Eng.

دوره 8  شماره 

صفحات  -

تاریخ انتشار 1996