Nikolaos F. Matsatsinis

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The purpose of this introductory part is to present an overall view of what MCDA<lb>is today. In Section 1, I will attempt to bring answers to questions such as: what<lb>is it reasonable to expect from MCDA? Why decision aiding is more often multi-<lb>criteria than monocriterion? What are the main limitations to objectivity? Section<lb>2 will be devoted to(More)
UTARec, a Recommender System that incorporates Multiple Criteria Analysis methodologies is presented. The system's performance and capability of addressing certain shortfalls of existing Recommender Systems is demonstrated in the case of movie recommendations. UTARec's accuracy is measured in terms of Kendall's tau and ROC curve analysis and is also(More)
Systems able to suggest items that a user may be interested in are usually named as Recommender Systems. The new emergent field of Recommender Systems has undoubtedly gained much interest in the research community. Although Recommender Systems work well in suggesting books, movies and items of general interest, many users express today a feeling that the(More)
A new methodology for the development of new products and an intelligent DSS, named MARKEX, which is an implementation of this methodology, are presented in this paper. The system acts as a consultant for marketers, providing visual support to enhance understanding and to overcome lack of expertise. The databases of the system are the results of consumer(More)
This article presents a robust, real-time background subtraction algorithm able to operate properly in complex dynamically changing visual conditions and indoor/outdoor environments, based on a single, cheap monocular camera, like a webcam. This algorithm uses an image grid and models each pixel of the grid as a mixture of adaptive Student-t distributions.(More)