Case-based reasoning: Market, applications, and fit with other technologies

摘要

Case-based reasoning (CBR), the hit of the American Association of Artificial Intelligence annual conference in 1991 and 1992 is now enjoying a surge of interest in its first year of commercial availability. Knowledge-based system designers, developers, integrators, and tool vendors are now seriously considering the role and utility of CBR in leveraging the vast experience within organizations for more effective decision making. The potential market for CBR appears enormous, particularly in more complex problem-solving domains, but the areas of most immediate interest are in applications where efficient information processing needs are urgent, such as automated help desks. Early experiments pairing CBR with rule-based systems will soon lead to hybrid combinations with other “close approximation” technologies, such as neural networks, fuzzy logic systems, genetic algorithms, and so forth. CBR appears headed for a sustaining role not only as a useful complement in knowledge-based information processing technology but also as an engine for “mainstream” information tasks of the future (e.g., intelligent text processing and retrieval, data mining, and projective reasoning). This article will discuss this emerging role for CBR and its implications from a marketing perspective.