Keynote Speakers
We are very pleased to have acquired the services of excellent keynote speakers for the conference. The speakers and the titles of their talks are shown below.
Prof Antonio Grilo
Universidade Nova de LisboaPortugal
Intelligent Decision Making in the Era of Semantic Web and Big Data
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Prof Dimitris K. Despotis
University of PiraeusGreece
Data Envelopment Analysis and performance measurement: Foundation and latest developments
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Prof Tomoko Kojiri
Kansai UniversityJapan
Knowledge-based Approach for Enhancing Collaborative Learning
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Other speaker's details to follow ...
Prof Antonio Grilo
Universidade Nova de LisboaPortugal
Intelligent Decision Making in the Era of Semantic Web and Big Data
Abstract:
Companies are facing today the availability of large amounts of data on the Web, issued by all sorts of sources, from RFIDs to Social Networks, but do not know how to use it to add value to their businesses. The challenge is on devising smart strategies that help managers to take the advantage, in an efficient way, of the available large amount of structured and unstructured information for intelligent decision-making. This implies designing and implementing automatic ways to gather, filter and analyze data from multiple sources on the Web and turn it into usable intelligence through decision making models. While large IT/software solution providers are starting to propose commercial solutions aimed at large corporations, this presentation will argue about the capability to address the challenge with less resourceful approaches.
Powerpoint presentation (5.6 Mbytes) available ..here..
Biography:
Holds a PhD degree in Industrial Management by the University of Salford, UK. He is an Assistant Professor of Industrial Engineering and Management at the Faculdade Ciências e Tecnologia da Universidade Nova de Lisboa, in doctoral, master and undergraduate degrees, lecturing Information Systems, Decision Models, and Economics Engineering. He has over 12 years of experience as a senior lecturer. He is a member of the board of directors of the research centre UNIDEMI. He has over 70 papers published in international scientific journals and conferences, and he is an expert for the European Commission DG-INFSO, and United Nations ITU.
Prof Dimitris K. Despotis
University of PiraeusGreece
Data Envelopment Analysis and performance measurement: Foundation and latest developments
Abstract:
Data Envelopment Analysis (DEA) is a non-parametric data-oriented approach for evaluating the performance of a set of peer entities, called decision making units (DMUs), which convert multiple incommensurable inputs into multiple outputs. DEA allows for great flexibility in defining the decision making units. Recent years have seen a large variety of applications of DEA for use in evaluating the performances of many different kinds of entities engaged in many different activities in many different contexts. As it requires very few assumptions, DEA has also opened up possibilities for use in cases that have been resistant to other approaches because of the complex (often unknown) relations between the multiple inputs and multiple outputs involved in the transformation processes of the DMUs. In the core of DEA is the identification of an efficient mix of DMUs that achieve specified levels of the outputs with the minimal use of inputs. The level of inputs used by the efficient mix is then compared with the actual inputs used by a DMU to produce its observed outputs. This comparison highlights whether the DMU under evaluation is efficient or not. The underpinning mathematical instrument of DEA is linear programming. The talk presents the fundamental principles and models of DEA followed by the most recent developments and extensions.
Biography:
Dimitris K. Despotis holds a BSc in Mathematics from the University of Athens and a PhD in Operations Research from the University of Piraeus. He is currently Professor of Decision Support Systems at the Department of Informatics, University of Piraeus, Greece. His specialization is in performance measurement and multi-criteria decision modelling. His current research focuses on data envelopment analysis and performance measurement. He has over 60 research papers published in various international scientific journals (Decision Support Systems, European Journal of Operational Research, Journal of the Operational Research Society, OMEGA Management Science, Journal of Information Technology and Decision Making, etc.) and conferences. He is member of international societies and working groups (European Working Group on Multiple Criteria Decision Making, European Summer Institute Group on Multi-criteria Analysis -ESIGMA, International Society on Multiple Criteria Decision Making, British Operational Research Society). He is a member of the editorial board of the Journal of Information and Optimization Systems, the International Journal of Applied Management and the International Journal of Multicriteria Decision Making, as well as member of the organizing and/or scientific committee of several international conferences.
Prof Tomoko Kojiri
Kansai UniversityJapan
Knowledge-based Approach for Enhancing Collaborative Learning
Abstract:
With introducing IT in schools, intelligent support for learning using computer has been widely developed. Computer-support learning contains interaction between learner and computer, so the system design should consider learners' personal differences of their understanding levels and characteristics. As the development of network technology, support for collaborative learning between learners in distributed environment is also focused. Collaborative learning support is the challenging task, since it should cope with complicate interactions among learners. Collaborative learning is a learning style in which learners acquire knowledge by exchanging opinions from others. To achieve better collaborative learning, supporting mechanism of acquiring knowledge as well as that of activating interaction should be developed. When learners collaboratively discuss experientially acquired knowledge, such as programming design, it is difficult to understand the merits/demerits of other learners' knowledge only from their opinions. Learners should consider meaning of the knowledge by themselves. In this talk, we introduce our approach for supporting collaborative learning with the communication support interface. Also, we introduce knowledge-based supporting mechanisms for understanding other learners' experiential knowledge deeply.
Biography:
Tomoko Kojiri is an Associate Professor in Department of Electrical and Electronic Engineering, Faculty of Engineering Science, Kansai University, Japan. She received her BE, ME and PhD in Engineering from Nagoya University in 1998, 2000 and 2003, respectively. Her research interests include computer-supported collaborative learning, intelligent tutoring system, meta-learning support system, and human-computer interface. She has received several awards, including outstanding paper award of ICCE/ICCAI 2000, and best paper award of KES 2005. She is a council of the Japanese Society for Information and Systems in Education. She is also a member of the editorial board of the Journal of Information and Systems in Education, the Japanese Society for Artificial Intelligence.