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We further develop our concept of a compound query (cf. Kacprzyk and Zadroižny [23]) in which in a bipolar query comprising of a required and desired condition aggregated via a non-conventional operator corresponding to “and if possible” the particular required and desired conditions are by themselves queries with fuzzy linguistic quantifiers. We use our approach to the dealing with data quality (trustworthiness),...
The paper concerns the problem of reaching consensus among agents in group decision making. A popular framework of individual preferences expressed as (fuzzy) preference relations is adopted. The consensus reaching process is assumed to be based on a discussion in the group of agents, which is expected to make the initially expressed preferences closer one to another. We present a novel approach to...
We propose a novel approach to the moderator supported consensus reaching process in a group of agents. We assume the agents' testimonies to be fuzzy preference relations, a fuzzy majority, and the concept of a degree of consensus meant as the degree to which, e.g., most of important agents agree as to almost all of relevant options. We use to handle fuzzy majorities Zadeh's calculus of linguistically...
We consider a particular type of text categorization problem which we refer to as the multiaspect classification. It is inspired by some practical scenario of business documents management in a company but has a broader application potential. A distinguishing feature of the new problem considered is the existence of two schemes of classification. The first one is based on the traditional, static set...
This work is meant as a step towards developing an effective and efficient procedure for a special type of the text categorization problem. A set of documents and a set of their categories are assumed. However, in addition to being assigned to a specific category, each document belongs to a certain sequence of documents, referred to as a case, comprising of documents from the same class. The problem...
A new type of linguistic summaries, so-called contextual linguistic summaries, are further developed. The point of departure are contextual bipolar queries which play the same role for a new type of summaries as flexible fuzzy queries do with respect to the classical linguistic summaries. The bipolar queries employed are of a special type, following the required/desired semantics formalized using...
We further develop our model of consensus reaching, and its related decision support system, that is based on the concept of a soft degree of consensus proposed by Kacprzyk and Fedrizzi, the idea of fuzzy preferences, and Kacprzyk's fuzzy majority. We assume that the process of consensus reaching proceeds in a (small) group of agents (decision makers, experts,…) who express their testimonies with...
In order to create a testbed for Computational Intelligence (CI) methods dealing with complex, non-deterministic and dynamic environments we propose a definition of a new class of problems, based on the real-world task of project scheduling and executing with risk management. Therefore, we define Risk-Aware Project Scheduling Problem (RAPSP) as a (significant) modification of the Resource-Constrained...
Recently a new line of research on database querying has been triggered by the observation that humans usually express their preferences using both positive and negative statements. This results in semantically richer bipolar queries consisting of conditions of the two types, where conditions of the former type express satisfactory or desired properties of data sought, while conditions of the latter...
Nowadays the amount of data is increasing very fast. Moreover, useful information is scattered over multiple sources. Therefore, automatic data integration that guarantees high data quality is extremely important. One of the crucial operations in integration of information from independent databases is detection of different representations of the same piece of information (called coreferent data)...
We present an idea of supporting the consensus reaching process, and its related group decision making process in a small group of autonomous decision makers (agents). Our approach is based on some fuzzy-logic-based representations, involving the use of fuzzy preference structure and linguistic quantifiers in a soft measure of the consensus, proposed by Kacprzyk and Fedrizzi, that is the degree to...
We are concerned with the so-called bipolar database queries which are meant here as those in which the query is composed of a necessary and optional part connected with a non-conventional aggregation operator “and possibly” as, for instance, in the query “find houses in a database of a real estate agency which are cheap and possibly close to a railroad station”. We first analyse some foundational...
The concept of bipolar linguistic summaries of data, introduced by Dziedzic, Zadrożny and Kacprzyk [1], is further developed. These summaries are meant as an extension of the “classical” linguistic summarization [2], [3], a human-consistent data mining technique, making it possible to express more complex patterns present in data. The focus of the paper is to provide a deeper insight into the very...
Preserving data quality is an important issue in data collection management. One of the crucial issues hereby is the detection of duplicate objects (called coreferent objects) which describe the same entity, but in different ways. In this paper we present a method for detecting coreferent objects in metadata, in particular in XML schemas. Our approach consists in comparing the paths from a root element...
We consider the important problem of comprehensiveness of linguistic data summaries equated with linguistically quantified propositions in Zadeh's sense. Motivated by Michal-ski's [29] seminal approach to the comprehensiveness of data mining and machine learning results, with a clear emphasis on natural language, we advocate the use of linguistic summaries which provide a new quality and an exceptional...
The quality measures for bipolar linguistic summaries of data, as proposed in our previous work [1], are further developed. The summaries introduced in [2] are assumed to be an extension of the “classical” linguistic summarization (cf. [3], [4]), a human-consistent data mining technique revealing complex patterns present in data. This extension consists in using the “and possibly” to build a summary...
The concept of a bipolar query, meant as a database query that involves both mandatory and optional conditions, is discussed from the point of view of, first, flexible database querying and, second, some newer approaches to decision making involving affects and judgments, unconventional multicriteria decision making and the modeling of sophisticated user's intentions and preferences of a positive...
Modern database systems allow to describe information from the real world in a well structured manner. Unfortunately, many databases cope with quality problems. One of these problems is the existence of coreferent data, which means that the same real world entity is described multiple times within one database. Due to errors, inaccuracies and lack of standardization, coreferent data are not bound...
We study the possibility to extend the concept of linguistic data summaries employing the notion of bipolarity. Yager's linguistic summaries may be derived using a fuzzy linguistic querying interface. We look for a similar analogy between bipolar queries and the extended form of linguistic summaries. The general concept of bipolar query, and its special interpretation are recalled, which turns out...
The concept of a bipolar query, meant as a database query that involves both positive and negative conditions is discussed from the point of view of flexible database querying. A new possible perspective is outlined which is related to the modeling of affects that play a crucial role in real world human centric decision making, and are also known to involve a positive and negative valuation which...
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