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This study addressed the literature gap, identified by other researchers, that there are too few examples of applied empirical open big data analytics. Using correspondence analysis as a big data analytical technique, this study demonstrates how qualitative big data type could be analyzed to identify hidden factor relationships that may assist strategic decision making. We use a 64MB open meta big...
Regression analysis is one of the components of data mining techniques. Various regression algorithms have been proposed to mine the data efficiently and to propose a suitable business model. Every algorithm caters to a particular need and not necessarily produces the best fit futuristic model for all types of data. On the other hand, todays Web is expanding rapidly and affecting all aspects of our...
Regression analysis is one of the techniques of data mining and is used to generate futuristic model for a given problem. One of the major challenge in the study of Regression analysis is to reduce the Outlier values. But the inherent complex and flexible nature of web data makes it difficult for various regression algorithms to propose an ideal futuristic model. This paper discusses a method that...
The distributive, concurrency and dynamic characteristics of service-oriented manufacturing model determine the activities of service-oriented manufacturing are in the environment of multi-relational data streams. In order to improve the service-oriented manufacturers' decision-making capacity, parallel efficiency and ability to adapt to the environment of multi-relational data streams, a framework...
Business intelligence may be defined as a set of mathematical models and analysis methodologies that systematically exploit the available data to retrieve information and knowledge useful in supporting complex decision-making processes. A business intelligence environment offers decision makers information and knowledge derived from data processing, through the application of mathematical models and...
Evaluating association rules is an integral post process in association rule mining. Association rules are examined by measures for their interestingness. Different interestingness measures have been proposed. Given an association rule mining task, measures are assessed and selected against a set of user-specified properties. However, in practice, due to the subjectivity and imperfection in property...
Decision tree, as an important classification algorithm in data mining, has been successfully applied in many fields. In this paper, based on the analysis of the essential characteristics of decision tree algorithm, we give a leaf criterion for multi-decision values of decision attribute, and establish a mathematical model for the selection for expanded attributes; also we give a concrete model based...
In order to avoid the risks associated with blind investment, especially in the current financial crisis, the demand forecast for the market has become very necessary. Data mining is the use of a variety of analysis tools found in the mass data of certain models and the relationship between the process data, it has become in all walks of life to solve the problem by means of an integral, the general...
Conceptual hierarchy represents the relationship between objects or concepts in a hierarchical form. The work presented here focuses on creating hierarchies which have a relationship between parent and child nodes but not between siblings. When we evaluate or classify certain objects (e.g., service quality), we often use a conceptual hierarchy which has various items (concept) at its nodes. If the...
Since Research and Development (R&D) projects portfolio decision deals with future events and opportunities, much of the information required making portfolio decisions is at best uncertain and at worst very unreliable. R&D projects are sometimes hard to be evaluated and selected. In this paper, a R&D projects portfolio selection decision system has been proposed based on data mining and...
With the significant increase in the number of Internet users of recent times, more digital content is being made and managed. Currently, digital content systems make videos utilizing key words and a content based retrieval process. This study proffers the concept of an automatic creation of story board by extracting emotional and content based data. Unlike previous systems, it provides a story board...
This thesis summarizes the factors which affect the mining investment environment through the introduction of investment environment, industry investment environment and mining investment environment and its characteristics. Also, this thesis sets up the corresponding three levels assessment system and AHP fuzzy comprehensive assessment mathematical model with an example of how it was used in environment...
This paper proposes modeling the rapidly evolving energy systems as cyber-based physical systems. It introduces a novel cyber-based dynamical model whose mathematical description depends on the cyber technologies supporting the physical system. This paper discusses how such a model can be used to ensure full observability through a cooperative information exchange among its components; this is achieved...
This paper proposes a probability weighted ARX (PrARX) model wherein the multiple ARX models are composed by the probabilistic weighting functions. As the probabilistic weighting function, a `softmax' function is introduced. Then, the parameter estimation problem for the proposed model is formulated as a single optimization problem. Furthermore, the identified PrARX model can be easily transformed...
The rapid development of the Internet has brought an opportunity for the development for enterprises. Web mining in the status of e-commerce Websites have became more and more important. In the e-commerce, the data mining is helpful of the discovery to trade development tendency, of the correct decision-making made by the enterprise. This article mainly summarizes the present electronic commerce's...
This paper focuses on the multiple attribute decision making problems with the attribute values being preference orderings and interval numbers evaluations. For the attributes with preference orderings evaluations, the fuzzy preference relation between the alternatives are calculated and the their rankings values are further normalized by measuring their relative distances to the ideal point; For...
This paper develops a supplier evaluation approach based on the analytic network process (ANP) and fuzzy synthetic evaluation under a fuzzy environment. The importance weights of various criteria are considered as linguistic variables. These linguistic ratings can be expressed in triangular fuzzy numbers by using the fuzzy extent analysis. Fuzzy synthetic evaluation is used to select a supplier alternative...
This paper focuses on the multiple attribute decision making problems with the attribute values being numeric, interval and linguistic evaluations. The decision matrix is normalized by calculating the grey relation coefficients of the interval and linguistic attribute values to their corresponding positive ideal ones. Furthermore, a mathematical programming model is set up to figure out the attribute...
The risks associated with making decisions based on poor-quality information are quite high. Consequently, the management of information quality (IQ) and the quality of associated information management processes has become critical for healthcare organizations. An important first step in managing information quality is the ability to measure the risk of information products based on the quality of...
This paper present a new method for multiple response optimization (MRO). Multiresponse problems comprise three stages: data gathering, model building and optimization. The most work in MRO don't consider the results of modeling stage while these outcomes can help in achieving the solution. In this paper, we incorporate the obtained results from stage of model building, i. e. the least significance...
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