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There are numerous problems of increasing significance where a pattern can have several classes simultaneously associated. This kind of problems, usually called multi-label problems, should be tackled with specific techniques in order to generate models more accurate than those obtained with classical classification algorithms. This work presents the adaptation of the J48 algorithm to multi-label...
Place recognition is a vital methodology for modeling environments and localizing autonomous mobile robots topologically. It can also be integrated in a hierarchical framework where it guides a fast and more precise metric position estimation. Especially for those hierarchical frameworks, it is crucial that the place recognition modules be highly accurate. In this paper, an information-theoretic approach...
In this paper we address the problem of how to measure information conveyed by an Atanassov's intuitionistic fuzzy set (A-IFS for short) and a related concept of knowledge that is explicitly context oriented and useful from the point of view of a specific purpose, notably related to decision making. We pay particular attention to the relationship between the positive and negative information and a...
In this paper we perform the analysis of Dempster-Shafer temporalized structure for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in Dempster-Shafer temporalized structure. The principle of negative inaccuracy is...
In recommender systems, the task of automatically deriving user profiles, encoding the actual preferences of users, covers a fundamental role. In this paper, we propose a strategy for learning and updating user profiles by using fuzzy sets that reveal to be a valid tool to model the vague and imprecise nature of preferences as well as the items to be recommended. The proposed adaptation strategy resembles...
This paper proposes a novel image fusion method that uses continuous Genetic Algorithm (CGA). Image fusion provides a single output image from a set of input images, captured from different viewing conditions, by different sensors, and at different times. Image fusion can be divided into three processing levels: pixel, feature and decision. Genetic algorithms are a nonlinear optimization technique...
The measurement of consensus and discrepancy among groups of evaluators is an important issue in group decision systems. These measurements will enable us to analyze the effort that should be made to obtain closer positions among subgroups. This paper presents a new approach, on the basis of the absolute order-of-magnitude qualitative model, to decision-making problems. The concepts of qualitative...
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