558 research outputs found

    Using Electronic Documents for Knowledge Acquisition and Model Maintenance

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    Knowledge acquisition and model maintenance are key problems in knowledge engineering to improve the productivity in the development of intelligent systems. Although historically a number of technical solutions have been proposed in this area, the recent experience shows that there is still an important gap between the way end-users describe their expertise and the way intelligent systems represent knowledge. In this paper we propose an original way to cope with this problem based on electronic documents. We propose the concept of intelligent document processor as a tool that allows the end-user to read/write a document explaining how an intelligent system operates in such a way that, if the user changes the content of the document, the intelligent system will react to these changes. The paper presents the structure of such a document based on knowledge categories derived from the modern knowledge modeling methodologies together with a number of requirements to be understandable by end-users and problem solvers

    The application of intelligent agents in libraries: a survey

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    Purpose - The purpose of this article is to provide a comprehensive literature review on the utilisation of intelligent agent technology in the library environment. Design/methodology/approach - Research papers since 1990 on the use of various intelligent agent technologies in libraries are divided into two main application areas: digital library (DL), including agent-based DL projects, multi-agent architecture for DLs, intelligent agents for distributed heterogeneous information retrieval and agent support to information search process in DLs; and services in traditional libraries, including user interface for library information systems, automatic reference services and multi-agent architecture for library services. For each paper on the topic, its new ideas or models, referred work, analyses, experiments, findings and conclusions are addressed. Findings - The majority of the literature covers DLs and there have been fewer studies about services in traditional libraries. A variety of architecture, framework and models integrating agent technology in library systems or services are proposed, but only a few have been implemented in the practical environment. The application of agent technology is still at the research and experimentation stage. Agent technology has great potential in many areas in the library context; however it presents challenges to libraries that want to be involved in its adoption. Practical implications - The survey has practical implications for libraries, librarians and computer professionals in developing projects that employ intelligent agent technology to meet end-users\u27 expectations as well as to improve information services within limited resources in library settings. Originality/value - The paper provides a comprehensive survey on the development and research of intelligent agents in libraries in literature

    Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

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    Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

    Web services choreography testing using semantic service description

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    Web services have become popular due to their ability to integrate with and to interoperate heterogeneous applications. Several web services can be combined into a single application to meet the needs of users. In the course of web services selection, a web candidate service needs to conform to the behaviour of its client, and one way of ensuring this conformity is by testing the interaction between the web service and its user. The existing web services test approaches mainly focus on syntax-based web services description, whilst the semantic-based solutions mostly address composite process flow testing. The aim of this research is to provide an automated testing approach to support service selection during automatic web services composition using Web Service Modeling Ontology (WSMO). The research work began with understanding and analysing the existing test generation approaches for web services. Second, the weaknesses of the existing approaches were identified and addressed by utilizing the choreography transition rules of WSMO in an effort to generate a Finite State Machine (FSM). The FSM was then used to generate the working test cases. Third, a technique to generate an FSM from Abstract State Machine (ASM) was adapted to be used with WSMO. This thesis finally proposed a new testing model called the Choreography to Finite State Machine (C2FSM) to support the service selection of an automatic web service composition. It proposed new algorithms to automatically generate the test cases from the semantic description (WSMO choreography description). The proposed approach was then evaluated using the Amazon E-Commerce Web Service WSMO description. The quality of the test cases generated using the proposed approach was measured by assessing their mutation adequacy score. A total of 115 mutants were created based on 7 mutant operators. A mutation adequacy score of 0.713 was obtained. The experimental validation demonstrated a significant result in the sense that C2FSM provided an efficient and feasible solution. The result of this research could assist the service consumer agents in verifying the behaviour of the Web service in selecting appropriate services for web service composition

    Digital steganalysis: Computational intelligence approach

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    In this paper, we present a consolidated view of digital media steganalysis from the perspective of computational intelligence.In our analysis the digital media steganalysis is divided into three domains which are image steganalysis, audio steganalysis, and video steganalysis.Three major computational intelligence methods have also been identified in the steganalysis domains which are bayesian, neural network, and genetic algorithm.Each of these methods has its own pros and cons

    Establishing Organizational Learning-Based System for Individual Using Self-Talk Therapy Approach: Case Study at Gula Padang Terap Sdn Bhd

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    This research investigates the elements that can encourage individuals to externalize and share tacit knowledge, which is critical in a continuous development of organizational learning-based information systems. To achieve this, self-talk therapy and proactive employee elements were utilized. The following objectives are proposed as a benchmark: (1) to develop the proactive employee elements in the respondents’ mindsets by using self-talk therapy training program; (2) to understand the roles of proactive employee elements in encouraging tacit knowledge externalization, sharing and documentation; (3) to investigate the roles of tacit knowledge externalization, sharing and documentation on a continuous information system (IS) database updates; and (4) to investigate the roles of IS database updates on organizational learning (OL). An in-depth case study approach was employed involving a manufacturing organization in Malaysia. The data was collected through interviews, observations, and documents review and analyzed using five-stage-hermeneutic analysis. The findings of this study indicated that the self-talk therapy training program were able to instill the proactive employee elements in the respondents’ mindsets. Being equipped with the proactive employee elements encourages the individuals to promote changes within their company. These elements in turn enable individuals to externalize, share and document tacit knowledge by producing ideas, actions, reactions and reflections. The documented tacit knowledge can be used to update organizational database. When the updated contents of organizational database are disseminated within the organization, a continuous learning is established. All these scenarios lead to the establishment of OL. This research offers a contribution to academic and business societies by presenting the elements that can encourage staff members to contribute inputs in terms of ideas, views or suggestions for OL-based IS development. This research also provides the decision makers with a platform that can reduce the dependency on the material rewards in motivating staff members

    Agile development in cloud computing for eliciting non-functional requirements

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    Agile is a popular and growing software development methodology. In the agile methodology, requirements are refined based on collaborations with customers and team members. However, the agile process faces a lack of visibility across the development and delivery processes, has complex and disjointed development processes and lacks communication agility between disconnected owners, development teams, and users. Furthermore, Non-Functional Requirements (NFR) are ignored due to the nature of agile development that lacks knowledge of the user and developer about NFR. In addition, extraction of the NFR is difficult and this difficulty is increased because the agile methodology promotes change in requirement at any stage of the development. Cloud computing services have helped solve some of the issues in the agile process. However, to address the issues in agile development, this research developed a framework for Agile Development in Cloud Computing (ADCC) that uses the facilitation of cloud computing to solve the above-mentioned issues. An Automated NFR eXtraction (ANFRX) method was developed to extract NFR from the software requirement documents and interview notes wrote during requirement gathering. The ANFRX method exploited the semantic knowledge of words in the requirement to classify and extract the NFR. Furthermore, an NFR Elicitation (NFRElicit) approach was developed to help users and development teams in elicitation of NFR in cloud computing. NFRElicit approach used components such as an organization’s projects history, ANFRX method, software quality standards, and templates. The ADCC framework was evaluated by conducting a case study and industrial survey. The results of the case study showed that the use of ADCC framework facilitated the agile development process. In addition, the industrial survey results revealed that the ADCC framework had a positive significant impact on communication, development infrastructure provision, scalability, transparency and requirement engineering activities in agile development. The ANFRX method was evaluated by applying it on PROMISE-NFR dataset. ANFRX method improved 40% and 26% in terms of f-measure from the Cleland and Slankas studies, respectively. The NFRElicit approach was applied to eProcurement dataset and evaluated in terms of more “Successful”, less “Partial Success” and “Failure” to identify NFR in requirement sentences. The NFRElicit approach improved 11.36% and 2.27% in terms of increase in “Successful” NFR, decrease of 5.68% and 1.14% in terms of “Partial success” and decrease of 5.68% and 1.13% in terms of “Failure” from the Non-functional requirement, Elicitation, Reasoning and Validation (NERV) and Capturing, Eliciting and Predicting (CEP) methodologies, respectively. The findings have shown the process was able to elicit and extract NFR for agile development in cloud computing
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