G. De Tré

Aggregating constraint satisfaction degrees expressed by possibilistic truth values

In information systems, one often has to deal with constraints in order to compel the semantics and integrity of the stored information or to express some querying criteria. Hereby, different constraints can be of different importance. A method to aggregate the information about the satisfaction of a finite number of constraints for a given data instance is presented. Central to the proposed method is the use of extended possibilistic truth values (to express the degree of satisfaction of a constraint) and the use of residual implicators and residual coimplicators (to model the impact and relevance of a constraint). The proposed method can be applied to any constraint-based system. A database application is discussed and illustrated.

A method based on shape-similarity for detecting similar opinions in group decision-making

In this paper, we propose a method to identify groups of similarly shaped membership functions representing criterion preferences provided by a large group of experts in the context of group decision-making. Our hypothesis hereby is that similarly shaped membership functions reflect similar expert opinions. The proposed method uses a symbolic notation to depict each membership function taking into account its shape characteristics (i.e., slopes and preference levels) and the relative length approximations on its X-axis segments (i.e., core segments, left and right spreads). The symbolic notation significantly reduces the complexity to handle a large group of expert opinions expressed by membership functions, and facilitates their comparison for grouping purposes through a shape-similarity measure. The main goal of the method is to detect all membership functions that are relevant to represent trends or suitable concepts among a large group of people considered as experts. An illustrative example, demonstrating the applicability of the method, is included in the paper.

A Possibilistic Approach to String Comparison

In this paper, comparison of strings is tackled from a possibilistic point of view. Instead of using the concept of similarity between strings, coreference between strings is adopted. The possibility of coreference is estimated by means of a possibilistic comparison operator. In literature, two important classes of comparison methods for strings have been distinguished: character-based methods and token-based methods. The first class treats a string as a sequence of characters, while the second class treats a string as a vector of substrings. The first contribution of this paper is to propose a new character-based method that is able to detect typographical errors and abbreviations. The main advantage of the proposed technique is the very low complexity in comparison with existing character-based techniques. In a second contribution, two-level systems are investigated and a new approach is described. The novelty of the proposed two-level system is the use of multiset comparison rather than vector comparison. It is shown how an ordered weighted conjunctive operator that uses a parameterized fuzzy quantifier to deliver weights is competitive with frequency-based weights. In addition, the use of a quantifier is significantly faster than the use of existing weight techniques. In a third contribution, a novel class of hybrid techniques is proposed that combines the advantages of several methods. Finally, comparative tests regarding accuracy and execution time are performed and reported.

On the Use of Case Based Reasoning Techniques in Flexible Querying

Case based reasoning (CBR) is a methodology where new problems are solved by investigating, adapting and reusing solutions to a previously solved, similar problem. Hereby knowledge is deduced from the characteristics of a collection of past cases, rather than induced from a set of knowledge rules that are stored in a knowledge base. In this paper we describe how fuzzy CBR techniques can be used to enhance the accessibility of relational databases, more specifically, flexible querying of regular relational databases. Two approaches are discussed: an approach where a database system is extended with a standalone instance- based prediction facility and an approach where such a prediction facility is embedded as an extension of the relational algebra. In both approaches, fuzzy set theory is used for the gradual modelling of similarity. Furthermore, its related possibility theory is used for the modelling of query satisfaction and for the handling of the inevitable uncertainty that occurs when predictions are made.

Fusion of preferences from different perspectives in a decision-making context

Our decision-making model recursively fuses preferences from different perspectives.It is suitable for different organizational structures based on a DMU concept.Propagation and fusion of preferences enriches the information.Enriched information allows a decision maker to make a more informed decision. Solving a decision-making problem about a brand-new product might include preferences from a high number of potential customers (e.g., followers of a company on social media) and managerial constraints (or preferences) given by corporate managers with regard to different aspects (i.e., economical, technical, environmental, etc.) over multiple criteria (e.g., weight, capacity, color, or usefulness of a product). These give us some new insights on fusing preferences given by persons having different perspectives (e.g., economical, technical, environmental, etc.), including decision-makers, and aimed to be suitable for different organizational structures (e.g., multilevel structures). Herein, a proper representation is needed to merge preferences from each perspective, enabling their propagation, throughout an organizational structure until the level in which a decision is made. This representation is presented as a decision-making unit (DMU), and is used as the primary component of our decision-making model. In this paper, we propose a novel decision-making model that recursively merges the preferred criteria from different DMUs using the logic scoring of preference (LSP) method. An illustrative example demonstrating the applicability of the proposed model, in the context of a new product design, is included in the paper.

Time management in fuzzy and uncertain object-oriented databases

The core of this chapter is the definition of a general object-oriented framework for the modelling of time and its use in the setting of fuzzy and uncertain object-oriented databases, in order to support the time concepts of transaction time, valid time and user-defined time and hence the traditional characteristics of temporal databases. The definition of this framework itself relies on a suitable, new theoretical time model that deals with the practical use of time indications in natural language.

Relevance Criteria for Spatial Information Retrieval Using Error-Tolerant Graph Matching

In this paper, we present a graph-based approach for mining geospatial data. The system uses error-tolerant graph matching to find correspondences between the detected image features and the geospatial vector data. Spatial relations between objects are used to find a reliable object-to-object mapping. Graph matching is used as a flexible query mechanism to answer the spatial query. A condition based on the expected graph error has been presented which allows determining the bounds of error tolerance and, in this way, characterizes the relevancy of a query solution. We show that the number of null labels is an important measure to determine relevancy. To be able to correctly interpret the matching results in terms of relevancy, the derived bounds of error tolerance are essential

Fuzzy time indications in natural languages interfaces

Common observations of the way in which time indications are used in natural language not only show that, very often, time is indicated in an approximative way, but also reveal the context-dependent precision with which time indications are expressed, relative to a kind of natural hierarchical time unit system.

Semantics and Modelling of Flexible Time Indications

This chapter presents an in-depth discussion of the semantics of time indications and proposes a formal time model suited to a variety of computer applications in which temporal databases play a role. The main characteristics of the model are the flexibility inherent to the ability of expressing approximate time indications in a way very close to natural language and the setting of a hierarchical framework, which allows to take into account the most appropriate level of granularity when expressing time indications.

A framework for flexible querying and mining of musical audio archives

In this paper the outline of a framework for the handling of flexible querying and mining of musical audio archives is presented. This framework has been designed within the scope of the DEKKMMA-project, which aims to build a digital musical audio archive for the ethnomusicological department of the Belgian Royal Museum for Central Africa. This museum holds one of the largest and world wide most important collections of music from Central Africa. Beside the digitizing and recording aspects, efficient access facilities for both specialized and nonspecialized users are required. In order to achieve this, the framework supports and integrates flexible querying, classification and object comparison mechanisms.