On Heterogeneous Database Retrieval: A Cognitively Guided Approach

Ramayya Krishnan, Xiaoping Li, David Steier, Leon Zhao

Information Systems Research · 2001 · Volume 12 · Issue 3

Abstract

Retrieving information from heterogeneous database systems involves a complex process and remains a challenging research area. We propose a cognitively guided approach for developing an information-retrieval agent that takes the user's information request, identifies relevant information sources, and generates a multidatabase access plan. Our work is distinctive in that the agent design is based on an empirical study of how human experts retrieve information from multiple, heterogeneous database systems. To improve on empirically observed information-retrieval capabilities, the design incorporates mathematical models and algorithmic components. These components optimize the set of information sources that need to be considered to respond to a user query and are used to develop efficient multidatabase-access plans. This agent design, which integrates cognitive and mathematical models, has been implemented using Soar, a knowledge-based architecture.

Keywords

Global Query Optimization, Heterogeneous Database Systems, Information Integration, Maximal Objects, Soar-Based AI Systems, Universal Relational Model

Enable JavaScript for citation tools and additional paper interactions.