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h Research 9 RESEARCH Main achievements of the project The main results of DECIDE are methodological, mathematical and algorithmical. In our naturalistic approach we extended the individual approaches to the collective decision problem through the setting up of multi-agent systems charged with analysing and assisting each of the decision makers present in a team (composed of few decision makers, following a common goal, in a cooperative manner). This approach permitted to broaden the search for solutions in the time given when decision makers risked remaining blocked on an individual basis. This approach allows to enlarge the search for solutions especially when the decision makers are blocked within their own individual scheme. The study of the flow of information and decisions at the heart of a group demonstrates the dynamic of the collective process and helps anticipate the classic behaviour of groups, such as, polarisation and extreme consensus [4]. Such behaviour is a source of numerous bad decisions which it is crucial to anticipate. Finally we propose the specifications of the central functions which a system of assistance must possess [5]. The type of decisions, the impact of the personality, the mood and the emotion of decision support systems are also studied. For multi-criteria systems we developed different mathematical models to elicit preferences, notably for upgrading [1] and for the theory of utility with the Choquet integral [6]. This work materialises in the form of the decisionmaking help KAPPALAB software under licence to CECILL. We propose five practical and necessary principles for constructive decisionmaking software. This work was developed for the choice problem (selection of a single alternative) with the RUBIS method which generalises a classic approach founded on the search for core choices [8]. We have proposed some criteria for evaluating the quality of data mining outputs, notably for the association rules. We systematise the study of the main objective measures on these criteria and other properties proposed in the literature. We supply a methodological framework and an aid to the decision for selection of measures so that the right measures are chosen [7]. We study closely the reference situations taken and generalise a large number of statistical measures [2]. This work leads us particularly to a generalisation of the functions founded on the entropy of Shannon. We then propose an adaptive strategy for the induction of decision trees, thus improving the performance of C4.5 one of the most popular tree induction algorithms and new class allocation rules for individuals. This algorithm improves the recognition of minority classes. We propose KEOPS, a methodology for integrating, in a coherent and uniform manner expert knowledge with the help of an ontology of the domain throughout the search process. The use of knowledge in biology and the main techniques of data mining for analysis of genes is discussed in [10]. Finally, in order to improve SONAR image recognition we propose to no longer use a single filter but to choose, for homogenous regions of images, the most suitable filter. Filtered images, because of the diversity of wavelet transformations and changes in associated representation spaces, are of better quality. Publications Chapters of Books [1] Patrick Meyer, Raymond Bisdorff, Jean-Luc Marichal. Disaggregation of bipolar-valued outranking relations. Modelling, computation and optimization in information systems and management sciences. Hoai An Le Thi, Pascal Bouvry and Tao Pham Dinh, Berlin, Heidelberg : Springer, 2008, (Communications in Computer and Information Science, 14), pp. 204-213, ISBN 978-3- 540-87476-8 [2] Benoît Vaillant, Stéphane Lallich, Philippe Lenca. On the behavior of the generalizations of the intensity of implication : a data-driven comparative study. Statistical implicative analysis : theory and applications, Berlin : Springer, 2008, (Studies in computational intelligence, 127), pp. 421-447, ISBN 978-3-540- 78982-6 109
esearc <strong>researResearch</strong> Publications Articles in peer-review journals [3] Raymond Bisdorff, Patrick Meyer, Yannis Siskos. OR and the management of electronic services-EURO'2004. European journal of operational research, june 2008, vol. 187, n° 3, pp. 1293-1295 [4] Frédéric Cadier, Gilles Coppin, Philippe Lenca. Decision makers support system. Adapting the assistance to the decision maker's behaviour. Ingénierie des systèmes d'information, march 2008, vol. 13, pp. 53-73 [5] Frédéric Cadier, Gilles Coppin, Philippe Lenca. Cognitive approach to distributed decision support systems. Foundations of computing and decision sciences, december 2008, vol. 33, n° 4, pp. 317-349 [6] Michel Grabisch, Ivan Kojadinovic, Patrick Meyer. A review of capacity identification methods for Choquet integral based multi-attribute utility theory, Applications of the Kappalab R package. European journal of operational research, april 2008, vol. 186, n° 2, pp. 766-785 [7] Philippe Lenca, Patrick Meyer, Benoît Vaillant, Stéphane Lallich. On selecting interestingness measures for association rules : user oriented description and multiple criteria decision aid. European journal of operational research, january 2008, vol. 184, n° 2, pp. 610-626 [8] Patrick Meyer, Raymond Bisdorff, Marc Roubens. Rubis: a bipolar-valued outranking method for the best choice decision problem. 4OR: A Quarterly Journal of Operations Research, june 2008, vol. 6, n° 2, pp. 143-165 [10] Nicolas Pasquier, Claude Pasquier, Laurent Brisson, Martine Collard. Mining Gene Expression Data using Domain Knowledge. International Journal of Software and Informatics, december 2008, vol. 2, n° 2, pp. 215-231 110
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