Maria Rifqi

Towards general measures of comparison of objects

We propose a classification of measures enabling to compare fuzzy characterizations of objects, according to their properties and the purpose of their utilization. We establish the difference between measures of satisfiability, resemblance, inclusion and dissimilarity. We base our study on concepts analogous to those developed by A. Tversky for his general work on similarities.

Interpolative reasoning based on graduality

We propose a new method to use an incomplete rule base with imprecise descriptions of variables. We extend classical interpolative reasoning to this case, under the assumption of graduality in variations of the variables, by using an analogical fuzzy approach.

A Similarity Measure between Basic Belief Assignments

A similarity measure between the focal elements used on a distance function of two basic belief assignments in the theory of evidence is presented, making way for the application of classical classification algorithms in this field. The properties of this measure are particular to its context, considering the characteristics of the focal elements, their relationship with each other and their proximity to the vacuous belief function that represents the state of total ignorance

Discrimination power of measures of comparison

This paper is based on a framework [3] for a formalization of measures of comparison of fuzzy objects. The purpose is to describe the behaviour of measures of comparison within a given family in order to facilitate the choice of a particular measure. It can be done owing to the discrimination power of a measure.

Fuzzy Prototypes: From a Cognitive View to a Machine Learning Principle

Cognitive psychology works have shown that the cognitive representation of categories is based on a typicality notion: all objects of a category do not have the same representativeness, some are more characteristic or more typical than others, and better exemplify their category. Categories are then defined in terms of prototypes, i.e. in terms of their most typical elements. Furthermore, these works showed that an object is all the more typical of its category as it shares many features with the other members of the category and few features with the members of other categories.

Expressions of graduality for sentiments analysis — A survey

Given the very ambiguous and imprecise nature of sentiments and of their expressions, this survey focuses on approaches making use of components of graduality in the task of automatic sentiments analysis. To that aim, we review methods taking account of intrinsic psychological models components of graduality as well as extrinsic components issued from computational intelligence approaches. In particular, beyond psychological models of sentiments that define affective states as multidimensional vectors in affective continuous spaces, we identify three components of graduality, namely composition or blending, intensity and inheritance. In our discussion, we review how fuzzy set theory as well as other gradual structures based on a vectorial representation are employed to describe affective states as complex or imprecise entities. Finally, we focus on verbal expressions of sentiments and more specifically, we discuss the use of components of graduality in order to deal with sentiments complex and subtle expressions issued from the expressive power of natural languages.

Real-World Fuzzy Logic Applications in Data Mining and Information Retrieval

This chapter focuses on real-world applications of fuzzy techniques for information retrieval and data mining. It gives a presentation of the theoretical background common to all applications, lying on two main elements: the concept of similarity and the fuzzy machine learning framework. It then describes a panel of real-world applications covering several domains namely medical, educational, chemical and multimedia.

Characterizing player's experience from physiological signals using fuzzy decision trees

In the recent years video games have enjoyed a dramatic increase in popularity, the growing market being echoed by a genuine interest in the academic field. With this flourishing technological and theoretical efforts, there is need to develop new evaluative methodologies for acknowledging the various aspects of the players subjective experience, and especially the emotional aspect. In this study, we addressed the possibility of developing a model for assessing the players enjoyment (amusement) with respect to challenge in an action game. Our aim was to explore the viability of a generic model for assessing emotional experience during gameplay from physiological signals. In particular, we propose an approach to characterize the players subjective experience in different psychological levels of enjoyment from physiological signals using fuzzy decision trees.

Uncertainty and Intelligent Information Systems

Intelligent systems are necessary to handle modern computer-based technologies managing information and knowledge. This book discusses the theories required to help provide solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of a linguistic nature. The main aspects of clustering, classification, summarization, decision making and systems modeling are also addressed. Topics covered in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, Bayesian networks and other network methods, as well as logic-based systems. Contents: Uncertainty Modeling; Clustering, Classification and Summarization; Decision Making and Information Processing; Systems Modeling and Applications; Logic and Mathematical Structures.

Towards a conscious choice of a fuzzy similarity measure: a qualitative point of view

In this paper, we propose to study similarity measures among fuzzy subsets from the point of view of the ranking relation they induce on object pairs. Using a classic method in measurement theory, introduced by Tversky, we establish necessary and sufficient conditions for the existence of a class of numerical similarity measures, to represent a given ordering relation, depending on the axioms this relation satisfies.