Sławomir Zadrożny

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The purpose of this paper is to propose the use of linguistic quantifiers for the linguistic summarisation of time series, notably in terms of trends. To characterize the data trends, we use three parameters: dynamics of change, duration and variability and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager. We Introduce(More)
The aim of this contribution is to present a prototype of decision support system based on mobile technologies and dynamic information. Users can run the system on their own mobile devices in order to provide their preferences at anytime and anywhere. The system provides consensual and selection support to deal with dynamic decision making situations.(More)
We present the use of fuzzy logic for the derivation of linguistic summaries of data (databases) for providing efficient and human consistent means for the analysis of large amounts of data to be used for a more realistic business decision support. We concentrate on the issue of how to measure the goodness of a linguistic summary, and on how to embed data(More)
The concepts of bipolar queries and queries with preferences are studied. Various interpretations of the former, recently defined by Dubois and Prade, are discussed. The latter was defined by Chomicki together with a new relational algebra operator winnow. The fuzzy version of the winnow operator is proposed. It is shown how it may be used to express a(More)
In this paper, we present the results of an experimental comparison of various aggregation operators used in a fuzzy information retrieval model we have recently proposed. The essence of this model is the use of Zadeh's linguistic statements to represent the documents and queries and then to determine their degree of matching. This leads to the use of the(More)
We present linguistic data summarization, meant as a process for a comprehensive description of big and complex data sets via short statements in natural language represented by protoforms in the form of linguistically quantified propositions dealt with using tools and techniques of fuzzy logic to grasp an inherent imprecision of natural language. Such(More)
This paper reports research into representing edge detectors, with the help of swarm intelligence [1]. Other gradient-based detectors may not produce the same edge pixels if applied onto the same image. Hence, the need of an edge detector arises, which is precise in detecting edges in majority of the common types of edges. The idea behind Swarm intelligence(More)
We consider our approach to the linguistic summarization of time series data proposed in our previous papers. We summarize trends identified here with straight segments of a piecewise linear approximation of time series. Then we employ, as a set of features, the duration, dynamics of change and variability, and assume different, human consistent(More)
The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data(More)
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