Synopsis
In the past, applied artificial intelligence systems were built with particular emphasis on general reasoning methods intended to function efficiently, even when only relatively little domain-specific knowledge was available. In other words, AI technology aimed at the processing of knowledge stored under comparatively general representation schemes. Nowadays, the focus has been redirected to the role played by specific and detailed knowledge, rather than to the reasoning methods themselves. Many new application systems are centered around knowledge bases, i. e. , they are based on large collections offacts, rules, and heuristics that cap- ture knowledge about a specific domain of applications. Experience has shown that when used in combination with rich knowledge bases, even simple reasoning methods can be extremely effective in a wide variety of problem domains. Knowledge base construction and management will thus become the key factor in the development of viable knowledge-based ap- plications. Knowledge Base Management Systems (KBMSs) are being proposed that provide user-friendly environments for the construction, retrieval, and manipUlation of large shared knowledge bases. In addition to deductive reasoning, KBMSs require operational characteristics such as concurrent access, integrity maintenance, error recovery, security, and perhaps distribution. For the development ofKBMSs, the need to integrate concepts and technologies from different areas, such as Artificial Intel- ligence, Databases, and Logic, has been widely recognized. One of the central issues for KBMSs is the framework used for knowledge representation-semantic networks, frames, rules, and logics are proposed by the AI and logic communities.
Synopsis
This book is based on material from current research projects and cooperations and from a recent workshop in the area of Knowledge Base Management Systems. It contains 25 revised papers and related discussions that concentrate on the integration of Database Technology (deductive databases, extended relational technology, object-oriented systems) and Artificial Intelligence (in particular logic programming and knowledge representation). The emphasis of the book is on the integration of DB/AI technology required for knowledge Base Management Systems. The book isolates major conceptual contributions, systems extensions, and reseach directions that lead towards that goal. This book is a European counterpart to another volume in the Topics in Information Systems Series, "On Knowledge Base Management Systems", resulting from a North American workshop and edited by M. Brodie and J. Mylopoulos, which concentrates on theoretical results and the more abstract levels of Knowledge Base Management.
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