Metasets and Opinion Mining in New Decision Support System

Kacprzak, Magdalena; Starosta, Bartłomiej; Węgrzyn-Wolska, Katarzyna

doi:10.1007/978-3-319-19369-4_55

Cited by 9 publications

(7 citation statements)

References 10 publications

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“…Recent development in applications of metasets is focused on decision systems [31][32][33]. There have been successful attempts to utilize metasets in character recognition problems [49,51].…”

Section: Metasetsmentioning

confidence: 99%

“…Labeling conditions with human language terms requires imposing partial ordering on these terms, which is generally rather subjective and not straightforward. We investigated such orderings in a series of papers discussing a new decision-support system based on this idea (see [31][32][33]). …”

Section: Applications Of Metasetsmentioning

confidence: 99%

“…Furthermore, they launched a new stream of research that has continued by his coworkers Kacprzak, Starosta, and Wȩgrzyn-Wolska after Kosiński's death. The applications of the research on OFNs and metasets concern not only approximate reasoning but also decision-support systems and opinion mining [31][32][33].…”

Section: Conclusion and Further Researchmentioning

confidence: 99%

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Two Approaches to Fuzzy Implication

Kacprzak

Starosta

2017

Theory and Applications of Ordered Fuzzy Numbers

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We discuss construction of fuzzy implication and also correlation between negation and implication operators defined on fuzzy values. Two structures for fuzzy implications are studied: the lattice of Step-Ordered Fuzzy Numbers (SOFNs) and the Boolean algebra B of membership degrees for metasets. Even though these two approaches stem from completely different areas it turned out that they lead to similar applications and results. Both of them emerged from research conducted by W. Kosiński and can be applied not only in the most popular application field which is approximate reasoning but also for designing decision-support systems, enriching methods and techniques of opinion mining, or modeling fuzzy beliefs in multiagent systems.

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Section: Metasetsmentioning

confidence: 99%

Section: Applications Of Metasetsmentioning

confidence: 99%

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Two Approaches to Fuzzy Implication

Kacprzak

Starosta

2017

Theory and Applications of Ordered Fuzzy Numbers

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“…This model was applied, among others, to support decision making [9,10,14], for presentation of revenues and costs of a company [2,3,7], in the Leontief model [1,2], for the presentation of stock prices [4,8,13], for the presentation of prices and the dynamics of their changes [5], and to determine the economic size of the delivery [6,11]. These applications are based on the orientation of the OFNs as additional information and the arithmetics of the OFNs similar to the arithmetics of real numbers.…”

Section: Introductionmentioning

confidence: 99%

Input-Output Model Based on Ordered Fuzzy Numbers

Kacprzak

2017

Theory and Applications of Ordered Fuzzy Numbers

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The chapter presents the application of Ordered Fuzzy Numbers (OFNs) to the economic model. These numbers are used for input-output analysis (the Leontief model), which is a basic method of quantitative economics that presents macroeconomic activity as a system of interrelated goods and services. OFNs allow us not only to apply mathematical modeling of imprecise or ambiguous data but also simultaneously portray more information than could be presented by real numbers. It is shown based on the Leontief model, where at the same time the current level, the forecast level, and the level of change of the final demand or the production level can be determined. The example shows that use of OFNs in economic modeling can simplify and deepen the economic analyses. IntroductionEconomics is a social science that studies and analyzes the production, distribution, and consumption of goods and services. One of the main tools used in economics is model. A model is a theoretical construction representing economic processes by a set of variables and a set of logical and quantitative relationships between them. Such model often take the form of systems of linear equations, due to their simplicity and ease of interpretation of their parameters and solution. One of the most famous and popular models of this type is the Leontief model, often called input-output analysis.Input-output analysis is a quantitative economic technique that represents interdependencies between different sectors (industries, branches) and a way of describing the allocation of resources of a national economy or different regional economies. It is a particularly effective tool for the optimization of production processes, the improvement of economic conditions, and cost allocation analysis.

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“…In comparison to existing methods, more accurate forecasting methods can be obtained using a rule-based forecasting (RBF), a technique combining data extrapolation [7,13,14,25,26,[43][44][45], time series [28,29,44,45], and elements of expert systems [5-7, 22, 23, 34, 37, 46]. The four most important methods of extrapolation were used: linear regression, random walk, and Brown's exponential smoothing, as well as Holt's exponential smoothing.…”

Section: Introductionmentioning

confidence: 99%

Detecting Nasdaq Composite Index Trends with OFNs

Zarzycki

Czerniak

Dobrosielski

2017

Studies in Fuzziness and Soft Computing

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The chapter presents a novel way of describing changes in the stock index and the identification of potential trends. The authors already used a similar approach to describe the stock exchange index [16]; this chapter is a continuation and another application of work on this issue. The method for detecting patterns in a trend by means of linguistic variables is described. The use of computational operations on numbers in the Ordered Fuzzy Number (OFN) notation [40][41][42] enables us to set the values of linguistic variables and thus conduct fuzzification of the input. By using one OFN number it is possible to store five parameters of index quotations (open, high, low, and close values as well as a change direction). The OFN numbers are conveyed into a linguistic form. In order to find trend sequence similarity the following applies: sequence identity with the input frame expressed as a percentage, frame size, the level of threshold conformity with the frame (threshold), and how often the pattern is present (frequency). A dedicated computer program to detect patterns is implemented. The program used data from the index Nasdaq Composite from the years 2006-2016. The results represent a further step to develop effective methods of rule-based forecasting.

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Metasets and Opinion Mining in New Decision Support System

Cited by 9 publications

References 10 publications

Two Approaches to Fuzzy Implication

Two Approaches to Fuzzy Implication

Input-Output Model Based on Ordered Fuzzy Numbers

Detecting Nasdaq Composite Index Trends with OFNs

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