A Min Tjoa

Bio: A Min Tjoa is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Data warehouse & Semantic Web. The author has an hindex of 32, co-authored 315 publications receiving 4795 citations. Previous affiliations of A Min Tjoa include Johannes Kepler University of Linz & University of Vienna.

E-Commerce and Web Technologies

Abstract: Existing electronic negotiation systems (ENSs) typically implement a single, fixed negotiation protocol, which restricts their use to negotiation problems that were anticipated and established a priori by the system designers. The single-protocol restriction limits ENSs’ applicability in experiments and in many real-life negotiation situations. ENSs that allow for the use of different protocols also allow for the customization to users’ needs and abilities. We present theoretical foundations for the design of flexible and highly customizable protocol-driven ENSs. Our design enables researchers and negotiators to map negotiation activities onto system components and to construct their own negotiation protocols by creating a sequence of layout programs invoking components and rules. * This work was supported with grants from the Initiative for New Economy of the Social Sciences and Humanities Research Council Canada, and the Natural Science and Engineering Research Council Canada. e-negotiations 2004 2

Current Advances, Trends and Challenges of Machine Learning and Knowledge Extraction: From Machine Learning to Explainable AI

Abstract: In this short editorial we present some thoughts on present and future trends in Artificial Intelligence (AI) generally, and Machine Learning (ML) specifically. Due to the huge ongoing success in machine learning, particularly in statistical learning from big data, there is rising interest of academia, industry and the public in this field. Industry is investing heavily in AI, and spin-offs and start-ups are emerging on an unprecedented rate. The European Union is allocating a lot of additional funding into AI research grants, and various institutions are calling for a joint European AI research institute. Even universities are taking AI/ML into their curricula and strategic plans. Finally, even the people on the street talk about it, and if grandma knows what her grandson is doing in his new start-up, then the time is ripe: We are reaching a new AI spring. However, as fantastic current approaches seem to be, there are still huge problems to be solved: the best performing models lack transparency, hence are considered to be black boxes. The general and worldwide trends in privacy, data protection, safety and security make such black box solutions difficult to use in practice. Specifically in Europe, where the new General Data Protection Regulation (GDPR) came into effect on May, 28, 2018 which affects everybody (right of explanation). Consequently, a previous niche field for many years, explainable AI, explodes in importance. For the future, we envision a fruitful marriage between classic logical approaches (ontologies) with statistical approaches which may lead to context-adaptive systems (stochastic ontologies) that might work similar as the human brain.

Performance Comparison between Naïve Bayes, Decision Tree and k-Nearest Neighbor in Searching Alternative Design in an Energy Simulation Tool

Abstract: Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. Commonly it has a feature providing alternative designs that are better than the user's design. In this paper, we propose a novel method in searching alternative design that is by using classification method. The classifiers we use are Naive Bayes, Decision Tree, and k-Nearest Neighbor. Our experiments hows that Decision Tree has the fastest classification time followed by Naive Bayes and k-Nearest Neighbor. The differences between classification time of Decision Tree and Naive Bayes also between Naive Bayes and k-NN are about an order of magnitude. Based on Percision, Recall, F- measure, Accuracy, and AUC, the performance of Naive Bayes is the best. It outperforms Decision Tree and k-Nearest Neighbor on all parameters but precision. Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. The output of such simulation is a value in kWh/m 2 called energy performance. The calculation of the building energy performance must be carried out by developers as part of requirements to get permit to build the building. The building can only be built if the energy performance is below the allowable standard. In order to get building energy performance below the standard, architects must revise the design several times. And in order to ease the design work of the architects, an energy simulation tool must have a feature that suggests a better alternative design. Since the alternative design search is actually a classification problem, hence in this paper we propose a novel method to search alternative design by using classification method. The classification methods used in here are Decision Tree, Naive Bayes, and k-Nearest Neighbor. We will then compare the performance of these three methods in searching alternative design in an energy simulation tools.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

World energy outlook

Abstract: This chapter discusses leading problems linked to energy that the world is now confronting and to propose some ideas concerning possible solutions. Oil deserves special attention among all energy sources. Since the beginning of 1981, it has merely been continuing and enhancing the downward movement in consumption and prices caused by excessive rises, especially for light crudes such as those from Africa, and the slowing down of worldwide economic growth. Densely-populated oil-producing countries need to produce to live, to pay for their food and their equipment. If the economic growth of the industrialized countries were to be 4%, even if investment in the rational use of energy were pushed to the limit and the development of nonpetroleum energy sources were also pursued actively, it would be extremely difficult to prevent a sharp rise in prices. It is evident that it is absolutely necessary to pursue actively the development of coal, natural gas, and nuclear power if a physical shortage of energy is not to block economic growth.