知识发现中一种变化趋势模型的算法研究

在时序数据库中,有许多成熟的技术和方法用来对布尔型属性之间的关系进行挖掘,但对于数值型属性变化趋势关联关系的研究却不是很多.本文提出了一种数值型属性变化趋势的研究模型QMP(QuantityMovementPattern),依据该模型可利用数据挖掘算法发现不同数值型属性之间变化趋势之间的关系.文中分析了该模型的几种实现算法,并给出了一种快速实现算法及实验数据.     

基于改进的模糊核C-均值算法在商业银行客户细分中的应用

随着商业银行信息化进程中数据集中阶段任务的完成,各商业银行将面临如何从大量的数据中提取有价值的信息和知识以提高企业决策质量和市场竞争力,数据挖掘技术的出现使企业“数据变知识”成为可能。文章主要结合商业银行的实际,探讨了核聚类方法在提高银行服务成功率等方面的应用。     

试题质量评价研究

教学过程的规范化管理是保证教学质量的重要手段。考试是对教和学的效果的检验，是教学过程管理规范化必须要解决的问题，一直受到教学管理部门的重视，采取了多项措施解决有关问题，其中一个重要的手段是采用试题库。在采用试题库时，必须要有高质量的试题作保证。本探讨基于KDD技术的试题质量评价方法和指标，并通过实例来说明其有效性。     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Solitary wave solutions of nonlinear financial markets :data-modeling-concept-practicing

This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely indicates a new science paradigm in the economy and society domains beyond physics.      

数据挖掘技术在银行业的应用

随着技术的进步、市场规模的扩大以及分工交易方式的发展,银行业的经营环境也因信息技术发展的影响而不断改变,银行业面临着愈加激烈的竞争.通过建立数据仓库,使用数据挖掘技术,挖掘出为银行创造利润的客户,从复杂的客户信息中建立模型,能够降低成本与风险,提高效益.     

零售业销售数据关联规则挖掘算法关键思想研究

对零售业销售数据关联规则挖掘算法的关键思想进行了研究，给出了各种提高算法效率的方法以及对规则选择的方法。     

试论村庄下采煤的技术问题

文章讨论了村庄下采煤的技术问题。     

Discovering Frequent Subtrees from XML Data Using Neural Networks

By rapid progress of network and storage technologies, a huge amount of electronic data such as Web pages and XML has been available on Internet. In this paper, we study a data-mining problem of discovering frequent ordered sub-trees in a large collection of XML data, where both of the patterns and the data are modeled by labeled ordered trees. We present an efficient algorithm of Ordered Subtree Miner （OSTMiner） based on two- layer neural networks with Hebb rule, that computes all ordered sub-trees appearing in a collection of XML trees with frequent above a user-specified threshold using a special structure EM-tree. In this algo- rithm, EM-tree is used as an extended merging tree to supply scheme information for efficient pruning and mining frequent sub-trees. Experiments results showed that OSTMiner has good response time and scales well.     

提高煤炭资源回收率实现矿井可持续发展

以同煤集团晋华宫矿为例,分析了提高煤炭资源回收率、合理开发矿井煤炭资源的途径。