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We develop an analysis method for genome-wide case-control association studies that is based on a polygenic threshold model. For each SNP in a given study, the risk allele is determined as that allele leading to an odds ratio greater than 1. For a given set of SNPs, the number of risk alleles in cases minus that in controls is evaluated and a p-value is obtained for this difference. For SNPs selected...
Machine Science, or Data-driven Research, is a new and interesting scientific methodology that uses advanced computational techniques to identify, retrieve, classify and analyse data in order to generate hypotheses and develop models. In this paper we describe three recent biomedical Machine Science studies, and use these to assess the current state of the art with specific emphasis on data mining,...
Summary form only only given. We consider the problem of assessing the significance of groups in high-dimensional data. In the case of supervised classification where there are data of known origin with respect to the groups under consideration, a guide to the degree of separation among the groups can be given in terms of the estimated error rate of a classifier formed to allocate a new observation...
The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, like data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image data set and experiment type and may thus require advanced image processing and classification...
In this work we present a software tool that allow identify tendencies that describe the evolution in a discipline of scientific knowledge, where information resources are classified. The tool search support the data mining as part of discovery knowledge process and the identification is supported by production analysis of information resources in science and technology and his visualization in graphs...
Future supermarkets will provide instrumented shopping carts, shelves and products so that large amounts of event data of customer's actions inside the store will be recorded. Special data mining algorithms will be necessary for analyzing this data effectively. At present, respective event data is not available. In order to create test data sets for developing, implementing and testing respective...
This paper use Microsoft SQL Server 2005 data mining tools and three methods of neural networks, decision trees and logistic regression to establish the financial crisis early-warning model of listed companies. The conclusion is that the three kinds of methods have good results and the prediction accuracy rate are 80% or more. The accuracy of the decision tree algorithm model is higher than others.
This paper demonstrated a case study on how to utilize time series analysis as mining tool to track the transience of fluoride release and to predict the fluoride concentration in groundwater. Southern Taiwan Science Park was selected as study area, and seven groundwater monitoring wells located in the domain of fluoride release were subjected to time series analysis. The measured fluoride levels...
Social networks of the Web 2.0 have become global (e.g. FaceBook, MSN). In 1977, L. C. FREEMAN published the first generic metrics for Social Networks Analysis (SNA), mainly based on static graph-mining models. The objective of our work is to introduce new dynamic SNA models dedicated to SNA and to take the conceptual aspects of enterprises and institutions social graph into account. Our work is based...
With the increasing level of volatility in the crude oil market, the transient data feature becomes more prevalent in the market and is no longer ignorable during the risk measurement process. Since using a set of bases available there are multiple representations for these transient data features, the sparsity measure based Morphological Component Analysis (MCF) model is proposed in this paper to...
As meta-synthesis approach is proposed to deal with complex system problem, the problem solving process under the meta-synthesis workshop is of importance. This paper discusses the working process of the meta-synthesis workshop which could be expressed as a three-dimension process consists of problem solving, expert collaboration and knowledge discovery (PS-EC-KD). Then, we propose a framework of...
This article is based on Data mining technology how to apply in the personal credit. Using decision tree algorithm, supporting data processing methods and more potential information for firms in order to facilitate business-to-customer to take a different credit programs.
With the fast development of information technology, both traditional audit theory and practice encounter the unprecedented challenge, hereafter the data audit conception emerges with respondence to these changes. Unfortunately the data audit model and its corresponding implementation route are scarcely studied. By integrating data mining technology with audit domain knowledge, this paper will proposed...
This article mainly introduces the design and implementation of DSS in business enterprise management. Focus on the management system and its function modules of DSS on commerce.
Individual credit risk has become the major risk of commercial banks in China all long. This paper proposes an Individual Credit Risk Evaluation System (ICRES) using data mining technology, with the aid of the concept of “feed forward control” in management theory as well as the reality in China. Using the information gain method to screen the alternative indicators and identify indicators that have...
In the management of land resources, reasonably controlling the amount of land use and making the land resources used intensively is an important measure to implement the dustainable development of land resources. Standing on the land use conditions of land resources, this article considers the business of examining land use as the main line. According to the problems which are possiblely existing...
Based on the present analytical method of Econometrics, this article conducts an empirical research on the co-movement of stock price of gold mine enterprises and the international gold price. By analyzing the daily datum from January 2th 2004 to October 20th 2009, the article concludes that there is a relative high correlation between the stock price of gold mine enterprises and the international...
In late of 1980s, when "customer-oriented" enterprises worked in competitive markets, a new paradigm entered in customer relationship management (CRM) scope that called customer lifetime value (CLV). CLV is the present value of all future profits for firms generated from a customer. CLV can be measured in different ways. According to recent researches, most of the proposed models are mathematical...
In many real-world topic detection tasks, the process of the topic detection is often interactive, which means the users are likely to interfere the reason process by expressing their preferences. We proposed an algorithm, iOLDA, and the software framework for interactive topic evolution pattern detection based on Latent Dirichlet Allocation (LDA). To abate those topics not interested or related,...
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