The journal of knowledge engineering special issue on WorldCist'17—fifth world conference on information systems and technologies

Abstract

In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if-then rules rather than through conventional procedural code. In this special issue, we present a range of articles covering some of the subareas of expert systems such as knowledge management, intelligent and decision support systems, ethics, computers, and security, health informatics, simulations, and big-data analytics. This special issue comprises six research papers. All manuscripts are extended versions of selected papers from WorldCIST'17-5th World Conference on Information Systems and Technologies, held in Porto Santo Island, Madeira, Portugal, in 2017. The WorldCIST conferences have become a global forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences, and concerns in the several perspectives of Information Systems and Technologies, as well as computer science in general. The six selected articles in this special section include an application game simulator, empirical study to name a few, as well as studies that focus more on the design and implementation of knowledge management and decision-making tools. Tiago Oliveira, Gonçalves, Novais, Satoh, and Neves (2019) OWL-based acquisition and editing of computer-interpretable guidelines [CIG] with the CompGuide editor, present the characterization of the current landscape of CIG as medium for the delivery of clinical decision support acquisition tools based on the properties of guideline visualization, organization, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, they described the CompGuide Editor, a tool for the acquisition of CIGs in their CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. Their editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition. João Carneiro, Martinho, Marreiros, and Novais (2019) how cognitive and affective aspects can influence the outcome of the group decision-making process, present mechanisms of automated negotiation, such as argumentation, that can be used in Ubiquitous Group Decision Support Systems to help decision makers find a solution based on their preferences. In this paper, they detailed a Ubiquitous Group Decision Support Systems architecture and explored two cognitive and affective methods that can be essential to the group decision-making process. They explained how agents can reason about self-expertise and other decision makers' credibility and how agents can verify and react to tendencies throughout the decision-making process. In their simulation environment that they tested for this work, agents that analysed credibility, expertise, and/or analysed tendencies always achieved a higher consensus compared with agents that used neither of the proposed methods. Likewise, agents that used neither of the proposed methods or only performed tendencies analysis obtained the worst average satisfaction levels for each simulation environment of decision-making. Habib and Marimuthu (2019) analysis of data trust through an intelligent-transparent-trust triangulation model, present a novel attempt to analyse the trustworthiness of computing sensor systems outcomes by modelling trust as an association triangle between intelligence, transparency, and trust in a sensor-based systems to establish the trustworthiness of data. They have proposed a triangulation model as a framework for assessing the trust and have selected two trust factors analogous to transparency and intelligence: the deviation of malfunctioning sensor data from its neighbours and the deviation from its own history. They have derived a set of relationships between the trust factors and their outcomes and have associated them with the proposed triangulation model. Furthermore, in the research, they formulated the generation of a trust subspace as an optimization problem with an objective function to maximize the trust. Tabu Search is then employed combined with Simulated Annealing to search for the best possible weighted combinations of trust factors. The authors have projected the experimental results onto a three-coordinate equilateral triangle to validate the decision analysis by displaying a definite trust or untrustworthiness of data. Faria, Ribeiro, Moreira, and Reis (2019) Boccia game simulator: Serious game adapted for people with disabilities, present their research about individuals with disabilities or motor disorders to feel more socially integrated, independent, and confident through integrating in the world of sports. This paper describes a realistic Boccia game simulator adapted for people with disabilities that integrates a set of features that includes real physics and social features. These features can be used to enhance the interest of nonpractitioners of the sport and to improve the training conditions. The official Boccia regulation was added to the design of the simulator. The usability and approximation to the reality of the simulator were tested and validated based on the tests performed and data collected via a survey of users with no motor or psychological disorders. Realism and usability rating was almost excellent, and good results were achieved at the assessment of the game experience. Gunel, Erdogdu, Polat, and Ozarslan (2019) an empirical study on evolutionary feature selection in intelligent tutors for learning concept detection, present concept map mining, which has emerged as a new research area with recent developments in computational intelligence in educational technology. The purpose of this study was to develop a mechanism using data-mining technique to determine the features that characterize a learning concept extracted automatically from a single educational text. The three major features that distinguish the real learning concepts from other sequences of strings are detected by using a hybrid system of a feed-forward neural network and some evolutionary algorithms. Ant colony optimization and genetic algorithm and particle swarm optimization are used as a binary feature selection method. In addition, the aforementioned methods are hybridized to get better accuracy and precision. The performance comparisons with two different state-of-the-art algorithms have been made from the viewpoint of a typical classification problem. This study enables researchers studying educational technology to gain time and space for learning concept detection for advancing concept map mining studies. It implies that there is no need to extract too many features for the problem, and to simplify the problem, it is enough to extract just a few features. Gonçalves, Rocha, Reis, and Barroso (2019) AppVox: An application to assist people with speech impairments in their speech therapy sessions, present in this study an application to assist people with speech impairments in their speech therapy sessions. AppVox simulates a vocalizer (audio stimulus feature) that can be used to train speech by repeating different words. In this paper, the authors presented the application as an assistive technology option and assessed it as a usable option for digital interaction for children with speech impairment. To assess the application, they have presented a case study in which the participants were asked to perform tasks using the AppVox application. The results showed that the group of participants attained a good performance when interacting with the application. The authors have further concluded that their designed application will help therapists, parents, and teachers of the special children in assessing which particular words the patients are having more difficulty in distinguishing. The application in the form of help provides patients to improve their pronunciation and helps specially the children to perform some exercises and also provide support to the parents for repetition of the exercises at home. Álvaro Rocha holds Habilitation in Information Science, PhD in Information Systems and Technologies, MSc in Information Management, and a BCs in Computer Science. He is Professor of Information Systems at the University of Coimbra and Honorary Professor at the Amity University, as well as a researcher at the Centre for Informatics and Systems of the University of Coimbra and a collaborative researcher at the Laboratory of Artificial Intelligence and Computer Science and at the Centre for Research in Health Technologies and Information Systems. His main research interests are Information Systems Planning and Management, Maturity Models, Information Systems Quality, Online Service Quality, Intelligent Information Systems, Software Engineering, e-Government, e-Health, and IT in Education. He is the President of the Iberian Association for Information Systems and Technologies and the Chair of the IEEE Portugal Section Systems, Man, and Cybernetics Society Chapter. He is also the Editor-in-Chief of both the Journal of Information Systems Engineering & Management and the Iberian Journal of Information Systems and Technologies. In addition, he has acted as Vice chair of Experts with the Horizon 2020 program of the European Commission, expert with the Italian Ministry of Education, Universities and Research, and expert with the Latvian Finances Ministry. Sajid Anwar is an Associate Professor in the Center of Excellence in Information Technology Institute of Management Sciences, Peshawar, Pakistan. He earned his BSc and MSc degree in computer science from University of Peshawar in 1997 and 1999, respectively. He completed MS degree (Computer Science, 2007) and PhD degree (Software Engineering, 2011) from NUCES-FAST, Islamabad. Currently, he is the Head of Undergraduate Program in Software Engineering at the Center of Excellence in Information Technology Institute of Management Sciences. Sajid Anwar is leading expert in Software Architecture Engineering and Software Maintenance Prediction. His research interests are cross-disciplinary and industry focused and includes search-based software engineering, prudent-based expert systems; customers churn prediction modelling, active learning and applying data mining and machine learning techniques to solve real-world problems. He has conducted and led collaborative research with Govt. organizations and academia. He has been a Guest Editor of numerous journals, such as Cluster Computing Journal Springer, Grid Computing Journal Springer, Expert Systems Journal Wiley, and Computational and Mathematical Organization Theory Journal Springer; Reviewer for IEEE Transactions on Evolutionary Computations, Neurocomputing Journal, IEEE Access, Expert Systems, Software: Practice and Experience, IEEE Transactions on Industrial Informatics, International Journal of Information Technology & Decision Making, and Telematics and Informatics Journal. He is also Member Board Committee Institute of Creative Advanced Technologies, Science and Engineering, Korea (iCatse.org) http://icatse.org/. As the guest editors, we are thankful to great researchers/scholars for their outstanding contributions to this special issue and reviewers for their timely and professional input. We would also take this opportunity to thank Jon Hall, Editor-in-Chief of the Wiley journal “Expert Systems.” In the end, we would extend our special gratitude and thanks to the WorldCIST'17 programme committee members for their hard work and dedication, which is highly commendable.

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