Clarifying Agreement Calculations and Analysis for End-User Elicitation Studies

We clarify fundamental aspects of end-user elicitation, enabling such studies to be run and analyzed with confidence, correctness, and scientific rigor. To this end, our contributions are multifold. We introduce a formal model of end-user elicitation in HCI and identify three types of agreement analysis: expert , codebook , and computer . We show that agreement is a mathematical tolerance relation generating a tolerance space over the set of elicited proposals. We review current measures of agreement and show that all can be computed from an agreement graph . In response to recent criticisms, we show that chance agreement represents an issue solely for inter-rater reliability studies and not for end-user elicitation, where it is opposed by chance disagreement . We conduct extensive simulations of 16 statistical tests for agreement rates, and report Type I errors and power. Based on our findings, we provide recommendations for practitioners and introduce a five-level hierarchy for elicitation studies.

Measures of Uncertainty for a Four-Hybrid Information System and Their Applications

A four-hybrid information system (4HIS) is an information system (IS) where the dataset of object descriptions consists of categorical, boolean, real-valued and missing data or attributes. This paper studies measures of uncertainty for a 4HIS and its application in attribute reduction. The distance function for each type of attribute in a 4HIS is first provided. Then, this distance is used to produce the tolerance relation induced by a given subsystem in a 4HIS. Next, information structure of this subsystem is proposed in terms of a set vector and dependence between information structures is introduced. Moreover, granulation and entropy measures in a 4HIS are investigated on the basis of information structures. In order to verify the feasibility of the proposed measures, effectiveness analysis is performed from a statistical perspective. Finally, an application of the proposed measures for attribute reduction in a 4HIS is given.

The relationship between tolerance for uncertainty and creativity among high school students with a critical style of thinking

The paper presents the results of a study of tolerance relation to uncertainty and creativity among senior schoolchildren with a critical style of thinking. The authors use valid diagnostic methods: A. Belousovas thinking style questionnaire, S. Badners uncertainty tolerance questionnaire, and P. Torrances test. The sample consists of 90 senior schoolchildren, both boys and girls. As a result of the study, the groups of schoolchildren with a dominant critical and practical style of thinking have been identified. The authors show that there are significant differences in the development of relationships between uncertainty and creativity tolerance scales, between uncertainty tolerance and critical thinking style, creativity and critical thinking style. The differences have been obtained in the development of tolerance for uncertainty, creativity in relation to the practical style of thinking.

Attribute selection approaches for incomplete interval-value data

Attribute selection in an information system (IS) is an important issue when dealing with a large amount of data. An IS with incomplete interval-value data is called an incomplete interval-valued information system (IIVIS). This paper proposes attribute selection approaches for an IIVIS. Firstly, the similarity degree between two information values of a given attribute in an IIVIS is proposed. Then, the tolerance relation on the object set with respect to a given attribute subset is obtained. Next, θ-reduction in an IIVIS is studied. What is more, connections between the proposed reduction and information entropy are revealed. Lastly, three reduction algorithms base on θ-discernibility matrix, θ-information entropy and θ-significance in an IIVIS are given.

JUMPING FROG METHOD FOR OPTIMAL CLASSIFICATIONS

In the article the problem of finding optimal classifications on a finite set is investigated. It is shown that the problem of finding an optimal classification is generated by a tolerance relation on a finite set. It is also reduced to an optimization problem on a set of permutations. It is proposed a modification of the mixed jumping frogs to find suboptimal solutions of the problem of classification.

Pattern classification using tolerance rough sets based on non-additive grey relational analysis and DEMATEL

PurposeIt is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance function to determine the tolerance relation. However, such a simple function does not take into account criterion weights and the interaction among criteria. Further, the traditional tolerance relation ignores interdependencies concerning direct and indirect influences among patterns. This study aimed to incorporate interaction and interdependencies into the tolerance relation to develop non-additive grey TRSCs (NG-TRSCs).Design/methodology/approachFor pattern classification, this study applied non-additive grey relational analysis (GRA) and the decision-making trial and evaluation laboratory (DEMATEL) technique to solve problems arising from interaction and interdependencies, respectively.FindingsThe classification accuracy rates derived from the proposed NG-TRSC were compared to those of other TRSCs with distinctive features. The results showed that the proposed classifier was superior to the other TRSCs considered.Practical implicationsIn addition to pattern classification, the proposed non-additive grey DEMATEL can further benefit the applications for managerial decision-making because it simplifies the operations for decision-makers and enhances the applicability of DEMATEL.Originality/valueThis paper contributes to the field by proposing the non-additive grey tolerance rough set (NG-TRS) for pattern classification. The proposed NG-TRSC can be constructed by integrating the non-additive GRA with DEMATEL by using a genetic algorithm to determine the relevant parameters.

Fuzzy Binary Rough Set

In this paper, we provide a definition of α-fuzzified lower and upper approximations for fuzzy sets based on the α-cut of fuzzy binary relations. We show that the definition is a proper generalization of the previous one for approximations of crisp sets and compare it with an existing definition in the context of fuzzy tolerance relation.

Many Faces of Lattice Tolerances

Our aim is to overview and discuss some of the most popular approaches to the notion of a tolerance relation in algebraic structures with the special emphasis on lattices.