Fundamenta Informaticae - Volume 132, issue 3

Authors: Li, Tianrui | Chen, Hongmei | Yao, JingTao | Nguyen, Hung Son

Article Type: Other

DOI: 10.3233/FI-2014-1044

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. i-iii, 2014

Authors: Deng, Xiaofei | Yao, Yiyu

Article Type: Research Article

Abstract: In situations where available information or evidence is incomplete or uncertain, probabilistic two-way decisions/classifications with a single threshold on probabilities for making either an acceptance or a rejection decision may be inappropriate. With the introduction of a third non-commitment option, probabilistic three-way decisions use a pair of thresholds and provide an effective and practical decision-making strategy. This paper presents a multifaceted analysis of probabilistic three-way decisions. By identifying an inadequacy of two-way decisions with respect to controlling the levels of various decision errors, we examine the motivations and advantages of three-way decisions. We present a general framework for computing the …required thresholds of a three-way decision model as an optimization problem. We investigate two special cases, one is a decision-theoretic rough set model and the other is an information-theoretic rough set model. Finally, we propose a heuristic algorithm for finding the required thresholds. Show more

Keywords: Three-way decisions, probabilistic rough sets, decision-theoretic rough sets, information-theoretic rough sets, information entropy, entropy minimization

DOI: 10.3233/FI-2014-1045

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 291-313, 2014

Authors: Pałkowski, Łukasz | Krysiński, Jerzy | Błaszczyński, Jerzy | Słowiński, Roman | Skrzypczak, Andrzej | Błaszczak, Jan | Gospodarek, Eugenia | Wróblewska, Joanna

Article Type: Research Article

Abstract: The paper investigates relationships between chemical structure, surface active properties and antibacterial activity of 70 bis-quaternary imidazolium chlorides. Chemical structure and properties of imidazolium chlorides were described by 7 condition attributes and antimicrobial properties were mapped by a decision attribute. Dominance-based Rough Set Approach (DRSA) was applied to discover a priori unknown rules exhibiting monotonicity relationships in the data, which hold in some parts of the evaluation space. Strong decision rules discovered in this way may enable creating prognostic models of new compounds with favorable antimicrobial properties. Moreover, relevance of the attributes estimated from the discovered rules allows to distinguish …which of the structure and surface active properties describe compounds that have the most preferable and the least preferable antimicrobial properties. Show more

Keywords: Structure Activity Relationship (SAR), Rough set theory, Dominance-based Rough Set Approach (DRSA), Confirmation measures

DOI: 10.3233/FI-2014-1046

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 315-330, 2014

Authors: Wang, Baoli | Liang, Jiye | Qian, Yuhua

Article Type: Research Article

Abstract: Choquet integral, as an adequate aggregation operator, extends the weighted mean operator by considering interactions among attributes. Choquet integral has been widely used in many real multi-attribute decision making. Weights (fuzzy measures) of attribute sets directly affect the decision results in multi-attribute decision making. In this paper, we aim to propose an objective method based on granular computing for determining the weights of the attribute sets. To address this issue, we first analyze the implied preorder relations under four evaluation forms and construct the corresponding preorder granular structures. Then, we define fuzzy measure of an attribute set by the similarity …degree between a special preorder pairs. Finally, we employ two numerical examples for illustrating the feasibility and effectiveness of the proposed method. It is deserved to point out that the weight of each attribute subset can be learned from a given data set by the proposed method, not but be given subjectively by the decision maker. This idea provides a new perspective for multi-attribute decision making. Show more

Keywords: preorder relation, granular computing, similarity degree, Choquet integral, multi-attribute decision making

DOI: 10.3233/FI-2014-1047

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 331-347, 2014

Authors: Wang, Guoyin | Guan, Lihe | Wu, Weizhi | Hu, Feng

Article Type: Research Article

Abstract: The classical rough set theory is based on the conventional indiscernibility relation. It is not very good for analyzing incomplete information. Some successful extended rough set models based on different non-equivalence relations have been proposed. The valued tolerance relation is such an extended model of classical rough set theory. However, the general calculation method of tolerance degree needs to know the prior probability distribution of an information system in advance, and it is also difficult to select a suitable threshold. In this paper, a data-driven valued tolerance relation (DVT) is proposed to solve this problem based on the idea of …data-driven data mining. The new calculation method of tolerance degree and the auto-selection method of threshold do not require any prior domain knowledge except the data set. Some properties about the DVT are analyzed. Experiment results show that the DVT can get better and more stable classification results than other extended models of the classical rough set theory. Show more

Keywords: rough set, valued tolerance relation, data-driven

DOI: 10.3233/FI-2014-1048

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 349-363, 2014

Authors: Clark, Patrick G. | Grzymala-Busse, Jerzy W. | Hippe, Zdzislaw S.

Article Type: Research Article

Abstract: The main objective of our research was to test whether the probabilistic approximations should be used in rule induction from incomplete data. For our research we designed experiments using six standard data sets. Four of the data sets were incomplete to begin with and two of the data sets had missing attribute values that were randomly inserted. In the six data sets, we used two interpretations of missing attribute values: lost values and “do not care” conditions. In addition we used three definitions of approximations: singleton, subset and concept. Among 36 combinations of a data set, type of missing attribute …values and type of approximation, for five combinations the error rate (the result of ten-fold cross validation) was smaller than for ordinary (lower and upper) approximations; for other four combinations, the error rate was larger than for ordinary approximations. For the remaining 27 combinations, the difference between these error rates was not statistically significant. Show more

DOI: 10.3233/FI-2014-1049

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 365-379, 2014

Authors: An, Shuang | Shi, Hong | Hu, Qinghua | Dang, Jianwu

Article Type: Research Article

Abstract: How to evaluate features and select nodes is one of the key issues in constructing decision trees. In this work fuzzy rough set theory is employed to design an index for evaluating the quality of fuzzy features or numerical attributes. A fuzzy rough decision tree algorithm, which can be used to address classification problems described with symbolic, real-valued or fuzzy features, is developed. As node selection, split generation and stopping criterion are three main factors in constructing a decision tree, we design different techniques to determine splits with different kinds of features. The proposed algorithm can directly generate a classification …tree without discretization or fuzzification of continuous attributes. Some numerical experiments are conducted and the comparative results show that the proposed algorithm is effective compared with some popular algorithms. Show more

Keywords: Fuzzy rough sets, decision trees, classification trees, splitting branches, uncertainty reasoning

DOI: 10.3233/FI-2014-1050

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 381-399, 2014

Authors: Zeng, Anping | Li, Tianrui | Zhang, Junbo | Chen, Hongmei

Article Type: Research Article

Abstract: The lower and upper approximations in rough set theory will change dynamically over time due to the variation of the information system. Incremental methods for updating approximations in rough set theory and its extensions have received much attention recently. Most existing incremental methods have difficulties in dealing with fuzzy decision systems which decision attributes are fuzzy. This paper introduces an incremental algorithm for updating approximations of rough fuzzy sets under the variation of the object set in fuzzy decision systems. In experiments on 6 data sets from UCI, comparisons of the incremental and non-incremental methods for updating approximations are conducted. …The experimental results show that the incremental method effectively reduces the computational time. Show more

Keywords: Rough Fuzzy Sets, Approximations, Incremental Learning, Fuzzy Decision System

DOI: 10.3233/FI-2014-1051

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 401-422, 2014

Authors: Świeboda, Wojciech | Krasuski, Adam | Nguyen, Hung Son | Janusz, Andrzej

Article Type: Research Article

Abstract: In this article we propose a general framework incorporating semantic indexing and search of texts within scientific document repositories. In our approach, a semantic interpreter, which can be seen as a tool for automatic tagging of textual data, is interactively updated based on feedback from the users, in order to improve quality of the tags that it produces. In our experiments, we index our document corpus using the Explicit Semantic Analysis (ESA) method. In this algorithm, an external knowledge base is used to measure relatedness between words and concepts, and those assessments are utilized to assign meaningful concepts to given …texts. In the paper, we explain how the weights expressing relations between particular words and concepts can be improved by interaction with users or by employment of expert knowledge. We also present some results of experiments on a document corpus acquired from the PubMed Central repository to show feasibility of our approach. Show more

Keywords: Semantic Search, Interactive Learning, Explicit Semantic Analysis, PubMed, MeSH

DOI: 10.3233/FI-2014-1052

Citation: Fundamenta Informaticae, vol. 132, no. 3, pp. 423-438, 2014