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320
A decision theoretic framework for approximating concepts
 International Journal of Manmachine Studies
, 1992
"... This paper explores the implications of approximating a concept based on the Bayesian decision procedure, which provides a plausible unification of the fuzzy set and rough set approaches for approximating a concept. We show that if a given concept is approximated by one set, the same result given by ..."
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Cited by 36 (20 self)
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This paper explores the implications of approximating a concept based on the Bayesian decision procedure, which provides a plausible unification of the fuzzy set and rough set approaches for approximating a concept. We show that if a given concept is approximated by one set, the same result given by the αcut in the fuzzy set theory is obtained. On the other hand, if a given concept is approximated by two sets, we can derive both the algebraic and probabilistic rough set approximations. Moreover, based on the well known principle of maximum (minimum) entropy, we give a useful interpretation of fuzzy intersection and union. Our results enhance the understanding and broaden the applications of both fuzzy and rough sets. 1.
Towards Instrument Segmentation for Music Content Description: A critical review of instrument classification techniques
 International Symposium on Music Information Retrieval
, 2000
"... this paper we concentrate on reviewing the different techniques that have been so far proposed for automatic classification of musical instruments. As most of the techniques to be discussed are usable only in "solo" performances we will evaluate their applicability to the more complex case of descri ..."
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Cited by 34 (4 self)
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this paper we concentrate on reviewing the different techniques that have been so far proposed for automatic classification of musical instruments. As most of the techniques to be discussed are usable only in "solo" performances we will evaluate their applicability to the more complex case of describing sound mixes. We conclude this survey discussing the necessity of developing new strategies for classifying sound mixes without a priori separation of sound sources
Information granulation and rough set approximation
 International Journal of Intelligent Systems
, 2001
"... Information granulation and concept approximation are some of the fundamental issues of granular computing. Granulation of a universe involves grouping of similar elements into granules to form coarsegrained views of the universe. Approximation of concepts, represented by subsets of the universe, d ..."
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Cited by 32 (15 self)
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Information granulation and concept approximation are some of the fundamental issues of granular computing. Granulation of a universe involves grouping of similar elements into granules to form coarsegrained views of the universe. Approximation of concepts, represented by subsets of the universe, deals with the descriptions of concepts using granules. In the context of rough set theory, this paper examines the two related issues. The granulation structures used by standard rough set theory and the corresponding approximation structures are reviewed. Hierarchical granulation and approximation structures are studied, which results in stratified rough set approximations. A nested sequence of granulations induced by a set of nested equivalence relations leads to a nested sequence of rough set approximations. A multilevel granulation, characterized by a special class of equivalence relations, leads to a more general approximation structure. The notion of neighborhood systems is also explored. 1
Semantic Translation Based on Approximate ReClassification
, 2000
"... We present a knowledgebased approachtointelligent information integration based on a reclassi#cation of information entities in a new context. We identify the needs of approaches performing semantic translation, weintroduce a uniform description of contexts and discuss a naive classi#cation a ..."
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Cited by 30 (9 self)
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We present a knowledgebased approachtointelligent information integration based on a reclassi#cation of information entities in a new context. We identify the needs of approaches performing semantic translation, weintroduce a uniform description of contexts and discuss a naive classi#cation approach. We argue that this approach makes unrealistic assumptions about the absence of uncertainty. Toovercome this problem we discuss several approximate classi#cation approaches and their use for information integration. Therebywe address symbolic as well as numeric approaches for uncertainty handling. We sumarize with a description of an actual application area and a discussion of open research topics.
Useful Feature Subsets and Rough Set Reducts
, 1994
"... In supervised classification learning, one attempts to induce a classifier that correctly predicts the label of novel instances. We demonstrate that by choosing a useful subset of features for the indiscernibility relation, an induction algorithm based on simple decision table can have high predicti ..."
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Cited by 26 (5 self)
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In supervised classification learning, one attempts to induce a classifier that correctly predicts the label of novel instances. We demonstrate that by choosing a useful subset of features for the indiscernibility relation, an induction algorithm based on simple decision table can have high prediction accuracy on artificial and realworld datasets. We show that useful feature subsets are not necessarily maximal independent sets (relative reducts) with respect to the label, and that, in practical situations, using a subset of the relative core features may lead to superior performance. 1 Introduction In supervised classification learning, one is given a training set containing labelled instances (examples) . Each labelled instance contains a list of feature values (attribute values) and a discrete label value. The induction task is to build a classifier that will correctly predict the label of novel instances. Common classifiers are decision trees, neural networks, and nearestneighbor...
A Partition Model of Granular Computing
 LNCS Transactions on Rough Sets
, 2004
"... There are two objectives of this chapter. One objective is to examine the basic principles and issues of granular computing. We focus on the tasks of granulation and computing with granules. From semantic and algorithmic perspectives, we study the construction, interpretation, and representation ..."
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Cited by 25 (6 self)
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There are two objectives of this chapter. One objective is to examine the basic principles and issues of granular computing. We focus on the tasks of granulation and computing with granules. From semantic and algorithmic perspectives, we study the construction, interpretation, and representation of granules, as well as principles and operations of computing and reasoning with granules. The other objective is to study a partition model of granular computing in a settheoretic setting. The model is based on the assumption that a finite set of universe is granulated through a family of pairwise disjoint subsets. A hierarchy of granulations is modeled by the notion of the partition lattice.
A Formal Model of the Process of Wayfinding in Built Environments
 In C. Freksa & D.M. Mark (Eds.), Spatial
, 1999
"... . Previous recent research on human wayfinding has focused primarily on mental representations rather than processes of wayfinding. This paper presents a formal model of some aspects of the process of wayfinding, where appropriate elements of human perception and cognition are formally realized ..."
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Cited by 21 (3 self)
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. Previous recent research on human wayfinding has focused primarily on mental representations rather than processes of wayfinding. This paper presents a formal model of some aspects of the process of wayfinding, where appropriate elements of human perception and cognition are formally realized using image schemata and affordances. The goaldriven reasoning chain that leads to action begins with incomplete and imprecise knowledge derived from imperfect observations of space. Actions result in further observations, derived knowledge and, recursively, further actions, until the goal is achieved or the wayfinder gives up. This paper gives a formalization of this process, using a modal extension to classical propositional logic to represent incomplete knowledge. Both knowledge and action are represented through a wayfinding graph. A special case of wayfinding in a building, that is finding one's way through an airport, is used to demonstrate the formal model. Keywords. Wayfind...
Granular Computing using Neighborhood Systems
 Advances in Soft Computing: Engineering Design and Manufacturing
, 1999
"... A settheoretic framework is proposed for granular computing. Each element of a universe is associated with a nonempty family of neighborhoods. A neighborhood of an element consists of those elements that are drawn towards that element by indistinguishability, similarity, proximity, or functionality ..."
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Cited by 21 (12 self)
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A settheoretic framework is proposed for granular computing. Each element of a universe is associated with a nonempty family of neighborhoods. A neighborhood of an element consists of those elements that are drawn towards that element by indistinguishability, similarity, proximity, or functionality. It is a granule containing the element. A neighborhood system is a family of granules, which is the available information or knowledge for granular computing. Operations on neighborhood systems, such as complement, intersection, and union, are defined by extending settheoretic operations. They provide a basis of the proposed framework of granular computing. Using this framework, we examine the notions of rough sets and qualitative fuzzy sets.
A RelationAlgebraic Approach to the Region Connection Calculus
 Fundamenta Informaticae
, 2001
"... We explore the relationalgebraic aspects of the region connection calculus (RCC) of Randell et al. (1992a). In particular, we present a refinement of the RCC8 table which shows that the axioms provide for more relations than are listed in the present table. We also show that each RCC model leads ..."
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Cited by 19 (0 self)
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We explore the relationalgebraic aspects of the region connection calculus (RCC) of Randell et al. (1992a). In particular, we present a refinement of the RCC8 table which shows that the axioms provide for more relations than are listed in the present table. We also show that each RCC model leads to a Boolean algebra. Finally, we prove that a refined version of the RCC5 table has as models all atomless Boolean algebras B with the natural ordering as the "part  of" relation, and that the table is closed under first order definable relations iff B is homogeneous. 1 Introduction Qualitative reasoning (QR) has its origins in the exploration of properties of physical systems when numerical information is not sufficient  or not present  to explain the situation at hand (Weld and Kleer, 1990). Furthermore, it is a tool to represent the abstractions of researchers who are constructing numerical systems which model the physical world. Thus, it fills a gap in data modeling which often l...
Granular Computing: An Emerging Paradigm
, 2001
"... We provide an overview of Granular Computing a rapidly growing area of information processing aimed at the construction of intelligent systems. We highlight the main features of Granular Computing, elaborate on the underlying formalisms of information granulation and discuss ways of their developme ..."
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Cited by 19 (0 self)
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We provide an overview of Granular Computing a rapidly growing area of information processing aimed at the construction of intelligent systems. We highlight the main features of Granular Computing, elaborate on the underlying formalisms of information granulation and discuss ways of their development. We also discuss the concept of granular modeling and present the issues of communication between formal frameworks of Granular Computing. © 2007 World Academic Press, UK. All rights reserved.