A novel method of "predicting" sitter case attribute value is presented in this paper. The method allows users to choose two attributes, seed and target attribute, and to predict the target attribute value of the forthcoming sitter case. The method first retrieves string sequences of the seed attribute according to filters the users set. Then, it finds the words in the sequences and calculates ...

When choosing between multiple alternatives, people usually do not have ready-made preferences in their mind but rather construct them on the go. The 2N-ary Choice Tree Model (Wollschlaeger & Diederich, 2012) proposes a preference construction process for N choice options from description, which is based on attribute weights, differences between attribute values, and noise. It is able to produc...

This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are ob...

The need of Data mining is because of the explosive growth of data from terabytes to petabytes. Data mining preprocess aims to produce the quality mining result in descriptive and predictive analysis. The quality of a clustering result depends on both the similarity measure used by the method and its implementation. A straightforward way to combine structural and attribute similarities is to us...

In this paper, we present the AbsMatcher system for schema matching which uses a graph based approach. The primary contribution of this paper is the development of new types of relationships for generating graph edges and the effectiveness of integrating schemas using those graphs. AbsMatcher creates a graph of related attributes within a schema, mines similarity between attributes in different...

Background: In this paper, a generic hesitant fuzzy set (HFS) model for clustering various ECG beats according to weights of attributes is proposed. A comprehensive review of the electrocardiogram signal classification and segmentation methodologies indicates that algorithms which are able to effectively handle the nonstationary and uncertainty of the signals should be used for ECG analysis. Ex...

Similarity plays a critical role in many judgments and choices. Traditional models of similarity posit that increasing the number of differences between objects cannot increase judged similarity between them. In contrast to these previous models, the present research shows that introducing a small difference in an attribute that previously was identical across objects can increase perceived sim...

Our work is motivated by and illustrated with application of association networks in computational biology, specifically in the context of gene/protein regulatory networks. Association networks represent systems of interacting elements, where a link between two different elements indicates a sufficient level of similarity between element attributes. While in reality relational ties between elem...