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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...
This paper investigates rough clustering of objects from uncertain databases using possibility and rough set theories. Real databases can contain both certain and uncertain attribute values. To properly cluster such instances into different clusters, it is necessary to take into account such uncertainty. When clustering objects with uncertain values, we have to consider the similarities between each...
This paper presents a proposal for a decision support system for the prevention of Intensive Care Unit readmissions, that is being built based on data from the MIMIC II database. The proposed system fuses the results of two distinct classification approaches, one based on available numerical data, and the other based on medical text annotations. The former uses neural fuzzy models and fuzzy modeling...
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...
Some probability distributions (e.g., Gaussian) are symmetric, some (e.g., lognormal) are non-symmetric (skewed). How can we gauge the skeweness? For symmetric distributions, the third central moment equation is equal to 0; thus, this moment is used to characterize skewness. This moment is usually estimated, based on the observed (sample) values equation as equation, where equation In many practical...
This study elaborates on a design of a face recognition algorithm realized with feature extraction from 2D-LDA and the use of polynomial-based radial basis function neural networks (P-RBF NNS). The overall face recognition system consists of two modules such as the preprocessing part and recognition part. The proposed polynomial-based radial basis function neural networks is used as an the recognition...
The aim of this paper is to introduce a set of procedures capable of produce a text summary from a causal graph. In previous works we have presented several algorithms to extract causal information from text documents by means of a semi-automatic process. As result we obtained a causal graph connecting concepts related to a given topic. In this paper we present a procedure capable of generating an...
Face recognition is a topic of great interest in different areas, especially those related to security. The identification of a person by the image of her face is a difficult task because of changes experienced by the face due to various factors, such as facial expression, aging and even the lighting. This paper presents a new face recognition technique based on the combination of a competitive fuzzy...
Construction projects have associated big amounts of, usually, unstructured data generated from several sources during the construction process. To be able to store these data in a structured database is a desired goal, for example, to assist project managers in the task of making better decisions based on these data. One of the most important document in this context is the bill of quantities, which...
The Fuzzy Joint Points (FJP) method which comprehends fuzziness in a level-based point of view is handled. At each iteration of the clustering process, unlike the classical fuzzy clustering in which the membership degrees of the points to the clusters are determined, the points which constitute the α-level sets are determined in FJP algorithm. In this study, some theoretical results are given for...
Skyline queries are a popular and powerful paradigm for extracting interesting objects from a d-dimensional dataset. They rely on Pareto dominance principle to identify the skyline objects, i.e., the set of incomparable objects which are not dominated by any other object from the dataset. Two main problems may be faced when using skyline queries: (i) a small number of returned objects which could...
Retrieving representative information from large-scale data becomes an important research issue nowadays. This paper focuses on certain aspects of representativeness in database queries and web search, and proposes an approach to extracting a subset of results from original search results in light of high coverage and low redundancy. In the paper, the notion of λ-Represent is introduced based on similarities...
The aim of this paper is to introduce procedure capable of compressing the representation of causal graphs, removing the redundant information introduced. In previous works we have presented several algorithms to extract causal information from text documents by means of a semi-automatic process. As result we obtained a causal graph connecting concepts related to a given topic.
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