Towards Intelligent Databases

This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

The use of abstraction concepts for representing and structuring documents

Due to the amount of documents available in modern offices, it is necessary to provide a multitude of methods for the structuring of knowledge, i.e., abstraction concepts. In order to achieve their uniform representation, such concepts should be considered in an integrated fashion to allow concise descriptions free of redundancy. In this paper, we present our approach towards an integration of methods of knowledge structuring. For this purpose, our view of abstraction concepts is briefly introduced using examples of the document world and compared with some existing systems. The main focus of this paper is to show the applicability of an integration of these abstraction concepts as well as their built-in reasoning facilities in supporting document processing and management

Policy Conflict Analysis in Distributed System Management

Accepted versio

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database