Ontologies Supporting Intelligent Agent-Based Assistance

Intelligent agent-based assistants are systems that try to simplify peoples work based on computers. Recent research on intelligent assistance has presented significant results in several and different situations. Building such a system is a difficult task that requires expertise in numerous artificial intelligence and engineering disciplines. A key point in this kind of system is knowledge handling. The use of ontologies for representing domain knowledge and for supporting reasoning is becoming wide-spread in many areas, including intelligent assistance. In this paper we present how ontologies can be used to support intelligent assistance in a multi-agent system context. We show how ontologies may be spread over the multi-agent system architecture, highlighting their role controlling user interaction and service description. We present in detail an ontology-based conversational interface for personal assistants, showing how to design an ontology for semantic interpretation and how the interpretation process uses it for semantic analysis. We also present how ontologies are used to describe decentralized services based on a multi-agent architecture

V-ROOM: a virtual meeting system with intelligent structured summarisation

With the growth of virtual organisations and multinational companies, virtual collaboration tasks are becoming more important for employees. This paper describes the development of a virtual meeting system, called V-ROOM. An exploration of facilities required in such a system has been conducted. The findings highlighted that intelligent systems are needed, especially since information that individuals have to know and process, is vast. The survey results showed that meeting summarisation is one of the most important new features that should be added to virtual meeting systems for enterprises. This paper highlights the innovative methods employed in V-ROOM to produce relevant meeting summaries. V- ROOM's approach is compared to other methods from the literature and it is shown how the use of meta-data provided by parts of the V-ROOM system can improve the quality of summaries produced

Tools for enterprises collaboration in virtual enterprises

Virtual Enterprise (VE) is an organizational collaboration concept which provides a competitive edge in the globalized business environment. The life cycle of a VE consists of four stages i.e. opportunity identification (Pre-Creation), partner selection (Creation), operation and dissolution. The success of VEs depends upon the efficient execution of their VE-lifecycles along with knowledge enhancement for the partner enterprises to facilitate the future formation of efficient VEs. This research aims to study the different issues which occur in the VE lifecycle and provides a platform for the formation of high performance enterprises and VEs. In the pre-creation stage, enterprises look for suitable partners to create their VE and to exploit a market opportunity. This phase requires explicit and implicit information extraction from enterprise data bases (ECOS-ontology) for the identification of suitable partners. A description logic (DL) based query system is developed to extract explicit and implicit information and to identify potential partners for the creation of the VE. In the creation phase, the identified partners are analysed using different risks paradigms and a cooperative game theoretic approach is used to develop a revenue sharing mechanism based on enterprises inputs and risk minimization for optimal partner selection. In the operation phases, interoperability remains a key issue for seamless transfer of knowledge information and data. DL-based ontology mapping is applied in this research to provide interoperability in the VE between enterprises with different domains of expertise. In the dissolution stage, knowledge acquired in the VE lifecycle needs to be disseminated among the enterprises to enhance their competitiveness. A DL-based ontology merging approach is provided to accommodate new knowledge with existing data bases with logical consistency. Finally, the proposed methodologies are validated using the case study. The results obtained in the case study illustrate the applicability and effectiveness of proposed methodologies in each stage of the VE life cycle

Guidelines for the usability evaluation of a BI application within a coal mining organization

Business Intelligence (BI) applications are consulted by their users on a daily basis. BI information obtained assist users to make business decisions and allow for a deeper understanding of the business and its driving forces. In a mining environment companies need to derive maximum benefit from BI applications, therefore these applications need to be used optimally. Optimal use depends on various factors including the usability of the product. The documented lack of usability evaluation guidelines provides the rationale for this study. The purpose is to investigate the usability evaluation of BI applications in the context of a coal mining organization. The research is guided by the question: What guidelines should be used to evaluate the usability of BI applications. The research design included the identification of BI usability issues based on the observation of BI users at the coal mining organization. The usability criteria extracted from the usability issues were compared and then merged with general usability criteria from literature to form an initial set of BI usability evaluation criteria. These criteria were used as the basis for a heuristic evaluation of the BI application used at the coal mining organization. The same application was also evaluated using the Software Usability Measurement Inventory (SUMI) standardised questionnaire. The results from the two evaluations were triangulated to provide a refined set of criteria. The main contribution of the study is the heuristic evaluation guidelines for BI applications (based on these criteria). These guidelines are grouped in the following functional areas: visibility, flexibility, cognition, application behaviour, error control and help, affect and BI elements.Information ScienceM.Sc. (Information Systems