Vladan Devedžić

A survey of modern knowledge modeling techniques

Abstract A major characteristic regarding developments in the broad field of artificial intelligence (AI) during the 1990s has been an increasing integration of AI with other disciplines. A number of other computer science fields and technologies have been used in developing intelligent systems, starting from traditional information systems and databases, to modern distributed systems and the Internet. This paper surveys the knowledge modeling techniques that have received most attention in recent years among developers of intelligent systems, AI practitioners and researchers. The techniques are described from two perspectives, theoretical and practical. Hence the first part of the paper presents major theoretical and architectural concepts, design approaches, and research issues. The second part deals with several practical systems, applications, and ongoing projects that use and implement the techniques described in the first part.

MDA-based Automatic OWL Ontology Development

This paper presents an eXtensible Stylesheet Language Transformation (XSLT)-based approach for automatic generation of the Web Ontology Language (OWL) from a UML model. Similar solutions that treat this problem are mostly partial since they do not use full metamodeling potentials. Although they emphasize the notion of the use UML for ontology development and propose necessary transformations into Semantic Web languages (e.g., RDF Schema, DAML, DAML+OIL), their UML models must be further refined using ontology-specialized tool. None of these approaches enables instance modeling and generation of OWL ontologies. In our efforts to make ontological and software engineering techniques closer, we have firstly defined ontology metamodeling architecture using Model Driven Architecture (MDA) concepts. This architecture consists of the Ontology Definition Metamodel defined using Meta Object Facility (MOF) and based on the OWL, as well as the related Ontology UML Profile (OUP). A transformation, that we present here, extends this metamodeling architecture and transforms an ontology from its OUP definition (i.e., XML Metadata Interchange – XMI) into the OWL description. Accordingly, we illustrate how an OUP-developed ontology can be shared with ontological engineering tools (i.e., Protégé).

Petri net ontology

Abstract The paper presents the Petri net ontology that enables sharing Petri nets on the Semantic Web. Previous work on formal methods for representing Petri nets mainly defines tool-specific descriptions or formats for model interchange. However, such efforts do not provide a suitable description for using Petri nets on the Semantic Web. This paper uses the Petri net UML model as a starting point for implementing the ontology. Resulting Petri net models are represented on the Semantic Web using XML-based ontology languages, RDF and OWL. We implemented a Petri net tool, P3, which can be used as a knowledge acquisition tool based on the Petri net ontology.

A UML profile for OWL ontologies

The paper presents Ontology UML Profile (OUP); which, together with Ontology Definition Metamodel (ODM), enables the usage of Model Driven Architecture (MDA) standards in ontological engineering. Other similar metamodels and UML profiles are based on ontology representation languages, such as RDF(S), DAML+OIL, etc. However, none of these other solutions uses the recent W3C effort - The Web Ontology Language (OWL). In our approach, we firstly define the place of ODM and OUP in the context of the MDA four-layer architecture and identify the main OWL concepts. Then, to support ODM, we define OUP and describe its details. The proposed UML profile enables usage of the well-known UML notation in ontological engineering more extensively. We implemented an XSLT that transforms OUP ontologies into OWL in order to provide a suitable tool support.

Expert systems in finance—a cross-section of the field

Abstract This paper surveys a number of well-known expert systems in the domain of finance. The idea is to illustrate the span of typical expert systems in finance and to provide an insight into the approaches and techniques they employ. The systems considered in the paper are all working systems, and come from different fields of finance. Specifically, the systems considered are FINEVA (from the field of financial analysis), PORT-MAN (banking management), INVEX (investment advisory) and FAME (financial marketing). The paper also briefly presents DEVEX, an expert system for currency exchange advising in international business transactions. Financial institutions in less-developed and undeveloped countries that deal with currency exchange often face some specific problems that do not exist in well-developed regions of the world. DEVEX helps bank employees to cope with such problems. Since business transactions between developed countries and Third World ones represent an important part of the worlds financial affairs, the problems covered in DEVEX go beyond local financial institutions.

Building an intelligent system using modern Internet technologies

Abstract This paper is a detailed case study of building Code Tutor, a Web-based intelligent tutoring system (ITS) in the domain of radio communications. It is ontologically founded and was built using CLIPS and Java-based expert system tools, latest integrated graphical CASE tools for software analysis and design, and Java servlets. In Code Tutor, Apache HTTP Server stores and serves static HTML pages, and Apache JServ Java package enables dynamic interpretation of user defined servlet classes and generation of active HTML pages. XML technology is used to generate files that Code Tutor uses to provide recommendations to the learners. Such a rich palette of integrated advanced technologies has greatly alleviated the system design and implementation, and has also led to interesting solutions of a number of problems common to many ITSs. The paper describes these solutions and useful design decisions, and discusses several practical issues related to architectures of intelligent Web-based applications.

JavaDON: an open-source expert system shell

Abstract The paper describes JavaDON, an open-source expert systems shell based on the OBOA framework for developing intelligent systems. The central idea of the JavaDON project was to make an easy-to-use and easy-to-extend tool for building practical expert systems. Since JavaDON is rooted in a sound theoretical framework, it is well-suited for building even complex expert system applications, both stand-alone and Web-based ones. JavaDON knowledge representation scheme supports using multimedia elements along with traditional techniques, such as rules and frames. Another important feature of JavaDON is its capability of saving knowledge bases in XML format (in addition to the shells native format), thus making them potentially easy to interoperate with other knowledge bases on the Internet. So far, JavaDON has been used to build several practical expert systems, as well as a practical knowledge engineering tool to support both introductory and advanced university courses on expert systems. The paper presents design details of JavaDON, explains its links with the underlying OBOA framework, and shows examples of using JavaDON in expert system development. It also discusses some of the current efforts in extending JavaDON.

LOCO-analyst: a tool for raising teachers' awareness in online learning environments

The paper presents LOCO-Analyst, an educational tool for providing teachers with feedback on the relevant aspects of the learning process taking place in a web-based learning environment. The feedback provision is based on the learning context, which we dubbed Learning Object Context and consider as a complex interplay of learning activities, learning objects, and learners. Here we present a usage scenario based on the real data obtained from the Web-based iHelp Courses Learning Content Management System, in order to illustrate some of the functionalities that LOCO-Analyst provides. We also briefly overview Semantic Web technologies that lay beneath LOCO-Analyst and make it a generic feedback provision tool. Related work is presented as well. The paper concludes with a sketch of our current and planned future efforts for further improving LOCO-Analyst.

Reusing Petri Nets Through the Semantic Web

The paper presents the Petri net ontology that should enable sharing Petri nets on the Semantic Web. Previous work on formal methods for representing Petri nets mainly defines tool-specific Petri net descriptions (i.e. metamodels) or formats for Petri net model interchange (i.e. syntax). However, such efforts do not provide a suitable model description for using Petri nets on the Semantic Web. This paper uses the Petri net UML model as a starting point for implementing the Petri net ontology. The UML model is then refined using the Protege ontology development tool and the Ontology UML profile. Resulting Petri net models are represented on the Semantic Web is using XML-based ontology representation languages, Resource Description Framework (RDF) and Web Ontology Language (OWL). We implemented a Petri net software tool as well as tools for the Petri net Semantic Web infrastructure.

Dynamic assembly of personalized learning content on the semantic web

This paper presents an ontology-based approach for automatic decomposition of learning objects (LOs) into reusable content units, and dynamic reassembly of such units into personalized learning content. To test our approach we developed TANGRAM, an integrated learning environment for the domain of Intelligent Information Systems. Relying on a number of ontologies, TANGRAM allows decomposition of LOs into smaller content units, which can be later assembled into new LOs personalized to the users domain knowledge, preferences, and learning styles. The focus of the presentation is on the ontologies themselves, in the context of user modeling and personalization. Furthermore, the paper presents the algorithm we apply to dynamically assemble content units into personalized learning content. We also discuss our experiences with dynamic content generation and point out directions for future work.