With the evolution of data mining systems, acquisition timely insights from unstructured text is an organizational demand which gradually increasing. The existing opinion systems have a variety properties, such as ranking products’ features and feature level visualizations; however, organizations require decision-making based upon customer feedback. Therefore, system proposed in this work that ...

The aim of this paper is to investigate the multiple attribute decision making problems with intuitionistic fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of intuitionistic fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional...

The aim of this paper is to present a hybrid group decision model for evaluating flexible manufacturing systems(FMSs), in which the information about attribute weights is completely unknown, and the attribute values take the form of triangular fuzzy numbers. In this proposed methodology, the voting method is adopted to calculate the attribute weights by aggregating the decision-makers’ attitude...

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The multi-attribute decision making problems are studied, in which the information about the attribute values take the form of uncertain linguistic variables. The concept of deviation degree between uncertain linguistic variables is defined, and ideal point of uncertain linguistic decision making matrix is also defined. A formula of possibility degree for the comparison between uncertain lingui...

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree...

Multi-attribute decision problems with uncertainty largely exist in the real world, it is very necessary to solve these problems. The paper proposes a grey correlation method based on maximizing deviation to solve the multiple attribute decision-making problems under risk in which the weight is unknown and attribute values are interval numbers. In the grey correlation method, according to diffe...

According to the characteristics of the large amount of QAR data,such as many parameters, time constraints, strong randomness and the problems of discrete data, together with attribute reduction and rules colleting during QAR anomaly detection, the paper proposed a anomaly detection algorithm of QAR data based on attribute support of rough set. Firstly, we discrete QAR data after converting the...

In this paper, we investigate the multiple attribute decision making (MADM) in uncertain linguistic setting where the information about attribute weights is incompletely known and the attribute values are uncertain linguistic variables, and the decision maker (DM) has preferences on alternatives. We establish two optimization models, which minimize deviations between the overall attribute valu...

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...