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Description: A complete business intelligence platform that includes reporting, analysis (OLAP), dashboards, data mining and data integration (ETL). Use it as a full suite or as individual components that are accessible via web services. Ranked #1 in open source BI. -A complete business intelligence platfor m that includes reporting, analysis (OLAP), dashboards. data mining and data integration (ETL). Use it a 's a full suite or as individual components that a 're accessible via web services. Ranked # 1 in ope n source BI.
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Size: 756421 |
Author: lyb |
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Description: Data mining (DM) is the extraction of hidden predictive information from large databases
(DBs). With the automatic discovery of knowledge implicit within DBs, DM uses
sophisticated statistical analysis and modeling techniques to uncover patterns and relationships
hidden in organizational DBs. Over the last 40 years, the tools and techniques to
process structured information have continued to evolve from DBs to data warehousing
(DW) to DM. DW applications have become business-critical. DM can extract even more
value out of these huge repositories of information.
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Size: 4267682 |
Author: 苏苏 |
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Description: ORACLE数据库有两类备份方法。第一类为物理备份，该方法实现数据库的完整恢复，但 数据库必须运行在归挡模式下（业务数据库在非归挡模式下运行），且需要极大的外部 存储设备，例如磁带库；第二类备份方式为逻辑备份，业务数据库采用此种方式，此方 法不需要数据库运行在归挡模式下，不但备份简单，而且可以不需要外部存储设备。 数据库逻辑备份方法 ORACLE数据库的逻辑备份分为三种模式：表备份、用户备份和完全备份-ORACLE database there are two types of backup methods. The first category of physical backup, the method to restore the integrity of the database, the database must be running naturalized block mode (Business Database in the naturalization of non-block mode operation), which requires a tremendous amount of external storage devices, such as tape libraries; The second category backup logical way to backup, database mining operations used this way, this method does not run on the database under block mode, the backup is not only simple, but can the need for an external storage devices. Logic database backup method ORACLE database, the logical backup divided into three patterns : Table backup, users backup and complete backup
Platform: |
Size: 3335 |
Author: zdq |
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Description: ORACLE数据库有两类备份方法。第一类为物理备份，该方法实现数据库的完整恢复，但 数据库必须运行在归挡模式下（业务数据库在非归挡模式下运行），且需要极大的外部 存储设备，例如磁带库；第二类备份方式为逻辑备份，业务数据库采用此种方式，此方 法不需要数据库运行在归挡模式下，不但备份简单，而且可以不需要外部存储设备。 数据库逻辑备份方法 ORACLE数据库的逻辑备份分为三种模式：表备份、用户备份和完全备份-ORACLE database there are two types of backup methods. The first category of physical backup, the method to restore the integrity of the database, the database must be running naturalized block mode (Business Database in the naturalization of non-block mode operation), which requires a tremendous amount of external storage devices, such as tape libraries; The second category backup logical way to backup, database mining operations used this way, this method does not run on the database under block mode, the backup is not only simple, but can the need for an external storage devices. Logic database backup method ORACLE database, the logical backup divided into three patterns : Table backup, users backup and complete backup
Platform: |
Size: 3072 |
Author: zdq |
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Description: A complete business intelligence platform that includes reporting, analysis (OLAP), dashboards, data mining and data integration (ETL). Use it as a full suite or as individual components that are accessible via web services. Ranked #1 in open source BI. -A complete business intelligence platfor m that includes reporting, analysis (OLAP), dashboards. data mining and data integration (ETL). Use it a 's a full suite or as individual components that a 're accessible via web services. Ranked# 1 in ope n source BI.
Platform: |
Size: 755712 |
Author: lyb |
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Description: Data mining (DM) is the extraction of hidden predictive information from large databases
(DBs). With the automatic discovery of knowledge implicit within DBs, DM uses
sophisticated statistical analysis and modeling techniques to uncover patterns and relationships
hidden in organizational DBs. Over the last 40 years, the tools and techniques to
process structured information have continued to evolve from DBs to data warehousing
(DW) to DM. DW applications have become business-critical. DM can extract even more
value out of these huge repositories of information.-Data mining (DM) is the extraction of hidden predictive information from large databases (DBs). With the automatic discovery of knowledge implicit within DBs, DM usessophisticated statistical analysis and modeling techniques to uncover patterns and relationshipshidden in organizational DBs. Over the last 40 years , the tools and techniques toprocess structured information have continued to evolve from DBs to data warehousing (DW) to DM. DW applications have become business-critical. DM can extract even morevalue out of these huge repositories of information.
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Size: 4267008 |
Author: 苏苏 |
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Description: 数据挖掘 案例开发 商业管理与决策分析的实例应用-Data Mining Case Development Business Management and Decision Analysis Application examples
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Size: 563200 |
Author: 王令 |
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Description: 蓝葵商业智能软件是一套全球功能最完备的商业智能软件产品之一，它是集查询(Query)、报表(Reporting)、分析(Analyze)、仪表盘经理(Dashboard Manager)、数据整合(Data Integration)及数据挖掘(Datamining)功能为一体的商业智能软件产品。 -Lan Kwai business intelligence software is the most comprehensive set of global business intelligence software products, it is a query (Query), statements (Reporting), analysis (Analyze), manager dashboard (Dashboard Manager), data integration (Data Integration) and Data Mining (Datamining) functions of business intelligence software products.
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Size: 33507328 |
Author: 刘永 |
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Description: Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.
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Size: 4617216 |
Author: Tthias |
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Description: 通过CRM系统分析、本公司需求分析及考察CRM的一般系统与实际业务流程关系，确定本公司CRM系统设计定位于基于部门应用、运营与分析并重。并在此系统设计目标定位下，确定系统流程，设计功能模块，并努力面向部门协作与数据挖掘。-Through the CRM system analysis, needs analysis the Company and the inspection of the general system CRM business processes and the actual relationship between the CRM system to determine the design of the Company located in sector-based applications, both operations and analysis. And targeting this system under design, the system processes, the design of function modules, and the efforts for collaboration and data mining sectors.
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Size: 30720 |
Author: waily |
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Description: 本书分为5个部分，共18章，较为全面地介绍了机器学习的基本概念，并讨论了数据挖掘和知识发现中的有关问题及多策略学习方法，具体地阐述了机器学习与数据挖掘在工程设计，文本、图像和音乐，网页分析、计算机病毒和计算机控制，医疗诊断、生物医疗信号分析和水质分析中的生物信号处理等方面的应用情况。 本书收集众多不同领域中数据挖掘的实际案例，以此来说明数据挖掘的具体解决方法，以期为广大读者提供一个更为广阔的数据挖掘应用视角。 本书的读者，可以是任何对机器学习与数据挖掘感兴趣的工程技术人员、业务管理人员，或是从事具体技术工作的其他人员。本书也可作为大专院校相关课程的重要辅导教材。-The book is divided into five parts, 18 chapters, more comprehensive introduction to the basic concepts of machine learning and discussed the Data Mining and Knowledge Discovery of the problem and multi-strategy learning methods, specifically on Machine Learning and Data Mining in engineering design, text, images and music, web analytics, computer viruses and computer control, medical diagnostics, biomedical signal analysis and water quality analysis in the areas of biological signal processing application. The book collection of many different areas of data mining in the actual case, in order to explain the specific data mining solution, with a view to providing readers with a broader perspective of data mining applications. The book s readers, can be any of the machine learning and data mining of interest to engineers, business managers, to engage in specific technologies or other staff. The book can also be used as the important institutions related courses supplementary teaching ma
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Size: 12882944 |
Author: 许兴明 |
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Description: 数据挖掘在商务中的应用,对商务数据的数据挖掘进行了详细描述-Data Mining in Business Applications, for business data, data mining is described in detail
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Size: 231424 |
Author: 谢超 |
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Description: Business Intelligence: Data Mining and Optimization for Decision Making
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Size: 2630656 |
Author: mshoseini |
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Description: A Data Mining Algorithm on E-business
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Size: 297984 |
Author: jalal |
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Description: This package contains a MATLAB implementation of the cluster
visualization tool CLUSION as described in
A. Strehl and J. Ghosh, "Relationship-based Clustering and
Visualization for High-dimensional Data Mining", Special
Issue on Mining Web-based Data for E-Business Applications
of the INFORMS Journal on Computing, 2002-This package contains a MATLAB implementation of the cluster
visualization tool CLUSION as described in
A. Strehl and J. Ghosh, "Relationship-based Clustering and
Visualization for High-dimensional Data Mining", Special
Issue on Mining Web-based Data for E-Business Applications
of the INFORMS Journal on Computing, 2002
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Size: 216064 |
Author: thirtyfive |
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Description: 一个可读的介绍，针对企业用户谁想要一个明确的，非技术的技术和数据挖掘功能的概述。一个有价值的教育工具，包括本公约所涵盖的令人振奋的新technology.Topics潜在用户的数据描述，数据挖掘，预测数据挖掘，数据挖掘模型和算法，数据挖掘过程中，选择数据挖掘产品。-A readable introduction aimed at business users who want a clear, non-technical overview of the techniques and capabilities of data mining. A valuable educational tool for prospective users of this exciting new technology.Topics covered include Data Description for Data Mining, Predictive Data Mining, Data Mining Models and Algorithms, The Data Mining Process, and Selecting Data Mining Products.
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Size: 206848 |
Author: David |
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Description: 数据
挖掘就是面对海量的存储数据建立数学模型，找出隐含的业务规则和有价值的信
息，在实际应用中发挥作用
-Data mining is the face of vast amounts of stored data to a mathematical model to identify the implicit business rules and valuable information to play a role in practical applications
Platform: |
Size: 7450624 |
Author: 毛玉凤 |
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Description: 数据挖掘是商务智能中经常使用的一项重要技术，企业在其整个运营过程中，积累了庞大的数据信息，决策者们所需要的信息往往就隐藏在里面，数据挖掘的目的就是如何有效地处理这些数据。论文结合数据挖掘软件Clementine分析了关联规则和聚类分析这两种算法在超市中的具体应用。-Data mining is an important technology,which is often used in business intelligence.Enterprises have accumulated large amount of data during the operation process,the information they need are usually hid in data mining.Therefore,how to deal with these data is the purpose of data mining.The essay,which analyzes the application of data mining in business intelligence ,combined with Clementine software to analyze the specific application of association rules and cluster analysis in the supermarket.
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Size: 107520 |
Author: 余承乐 |
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Description: Although most business processes change over time, contemporary process mining techniques tend to analyze these processes as if they are in a steady state. Processes may change suddenly or gradually. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). For the process management, it is crucial to discover and understand such concept drifts in processes. This paper presents a generic framework and specific techniques to detect when a process changes and to localize the parts of the process that have changed. Different features are proposed to characterize relationships among activities.
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Size: 20141056 |
Author: pravin |
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Description: 数据挖掘的入门级教材，非常适用信息管理与信息系统专业同学学习-Entry level data mining materials, ideal for information management and information systems students to learn
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Size: 15582208 |
Author: kukumalu |
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