Conceptual information processing: A robust approach to KBS-DBMS integration

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing

Decision support systems (DSS) are becoming increasingly more critical to the daily operation of organizations. Data warehousing, an integral part of this, provides an infrastructure that enables businesses to extract, cleanse, and store vast amounts of data. The basic purpose of a data warehouse is to empower the knowledge workers with information that allows them to make decisions based on a solid foundation of fact. However, only a fraction of the needed information exists on computers; the vast majority of a firm’s intellectual assets exist as knowledge in the minds of its employees. What is needed is a new generation of knowledge-enabled systems that provides the infrastructure needed to capture, cleanse, store, organize, leverage, and disseminate not only data and information but also the knowledge of the firm. The purpose of this paper is to propose, as an extension to the data warehouse model, a knowledge warehouse (KW) architecture that will not only facilitate the capturing and coding of knowledge but also enhance the retrieval and sharing of knowledge across the organization. The knowledge warehouse proposed here suggests a different direction for DSS in the next decade. This new direction is based on an expanded purpose of DSS. That is, the purpose of DSS in knowledge improvement. This expanded purpose of DSS also suggests that the effectiveness of a DS will, in the future, be measured based on how well it promotes and enhances knowledge, how well it improves the mental model(s) and understanding of the decision maker(s) and thereby how well it improves his/her decision making

Integration of document representation, processing and management

This paper describes a way for document representation and proposes an approach towards an integrated document processing and management system. The approach has the intention to capture essentially freely structured documents, like those typically used in the office domain. The document analysis system ANASTASIL is capable to reveal the structure of complex paper documents, as well as logical objects within it, like receiver, footnote, date. Moreover, it facilitates the handling of the containing information. Analyzed documents are stored by the management system KRISYS that is connected to several different subsequent services. The described integrated system can be considered as an ideal extension of the human clerk, making his tasks in information processing easier. The symbolic representation of the analysis results allow an easy transformation in a given international standard, e.g., ODA/ODIF or SGML, and to interchange it via global network

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