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pub:research:fedcsis2012

FedCSIS 2012 Tutorial - Semantic Knowledge Engineering for Business Intelligence: concepts and tools

The workshop is targeted on a broad audience familiar with methods of Artificial Intelligence and Business Intelligence. It is intended to give a theoretical background as well as practical approach and tools. It can also serve as a source of inspiration both for researchers involved in this and similar domain and PhD students working in the area of Knowledge Engineering and Software Engineering. Representatives of industry and members of software management staff are also cordially welcome.

Instructors
Name Email Phone Website
Grzegorz J. Nalepa gjn@agh.edu.pl 12 617 38 56 http://home.agh.edu.pl/~gjn
Antoni Ligęza ligeza@agh.edu.pl 12 617 28 49 http://home.agh.edu.pl/~ligeza
Krzysztof Kaczor kk@agh.edi.pl 12 617 39 41 http://home.agh.edu.pl/~kk
Szymon Bobek szymon.bobek@agh.edu.pl 12 617 39 41 http://home.agh.edu.pl/~sbobek
Weronika T. Adrian wta@agh.edu.pl 12 617 50 64 http://home.agh.edu.pl/~wta
Krzysztof Kluza kluza@agh.edu.pl 12 617 50 64 http://home.agh.edu.pl/~kluza

Abstract

Knowledge-Based Systems are an important class of intelligent systems originating from the field of Artificial Intelligence, and now widely used in business and industry. In the creation of such systems a number of knowledge formalization and representation methods are used. Recently there has been a growing interest in the use of the socalled Business Rules in such systems. Moreover, the rules need to be aligned and integrated with the Business Processes of an enterprise. The semantics of such a heterogeneous systems is often captured with the use of Formal Ontologies providing a common vocabulary for business concepts. Design, analysis and deployment of such systems remains a great challenge for knowledge engineers and business software architects. The tutorial presents a coherent methodology capturing knowledge representation, knowledge management and application with focus on semantic aspects – the Semantic Knowledge Engineering approach. It supports design, verification and deployment of knowledge base systems that integrate rules, process and ontologies using a formalized framework for knowledge representation and processing. During the tutorial the conceptual foundations of the methodology are given, including the hierarchical design process, concept formalization with the ALSV(FD) logic, and rule representation with the XTT2 method. Then a number of practical methods and tools for a visual and collaborative modeling rules and business process based on ontologies are given. Finally, the applications of this approach in the field of Business Intelligence are discussed and presented.

Table of Content

  1. SKE: Introduction, Concepts, and Design Process. (Grzegorz J. Nalepa - gjn@agh.edu.pl )
  2. Rule Formalization with ALSV(FD) and XTT2. (Antoni Ligęza - ligeza@agh.edu.pl)
  3. Visual Rule Modeling with HQEd. (Krzysztof Kaczor - kk@agh.edi.pl )
  4. Rule Execution in HeaRT. (Szymon Bobek - szymon.bobek@agh.edu.pl)
  5. Integrating Rules with Processes towards Semantic Business Intelligence. (Krzysztof Kluza - kluza@agh.edu.pl )
  6. Knowledge Modeling with Loki. (Weronika T. Adrian - wta@agh.edu.pl)

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pub/research/fedcsis2012.txt · Last modified: 2013/01/10 13:57 (external edit)