Data Mining - Analysis - IT Library : ZDNet Asia

White Papers

Case Studies

Vendor Webcast

Show all content

Title Date Added Company

How Profitable to You Is Each Customer Today... and Tomorrow?: Why Transactional Profitability Measurements Are an Ultimate Goal 2007-03-01 SAS Institute

The problem with accounting's traditional gross profit margin reporting (i.e., restricted to product cost profit margins) is that managers cannot see the bottom half of the total picture - all the profit margin layers eroded from distribution, selling, credit, payments and marketing costs. The unacceptable result from not converting these types of expenses into customer costs is executives, managers and employee teams receive incomplete profit reporting that is not segmented by customer - and the product profitability data they do receive is flawed and misleading. This white paper describes a solution to these deficiencies. It describes a powerful and economical managerial accounting system that collects and transforms data at the detailed transaction level.

Tags: Accounting Applications, Business Intelligence - Data Warehousing

Data Mining Techniques for (Network) Intrusion Detection Systems 2007-01-12 University of California

In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion detection does not, in general, include prevention of intrusions. This paper mostly focused on data mining techniques that are being used for such purposes. It debates on the advantages and disadvantages of these techniques. Finally the paper presents a new idea on how data mining can aid IDSs.

Tags: Security Tools, Intrusion Detection Systems

Training Teachers Across a Diversity of Contexts: An Analysis of International Evaluation Data on the Intel Teach Essentials Course, 2006 2007-01-01 Intel

The Intel Education Initiative seeks to form a trusted partnership with ministries of education in countries across the world to support educational reform by integrating technology into project-based learning environments. As part of the partnership, Intel also offers a portfolio of teacher professional development programs. The Intel Education Initiative has consistently invested in the evaluation of the Essentials Course worldwide, both to inform the continuous improvement of the program and its implementation model, and to document and demonstrate the impact of the program on its teacher participants. This report on the global evaluation of the Essentials Course draws on data from both quantitative evaluations done in many countries and qualitative reports that are often part of the local evaluation.

Tags: Career Development, Courseware

Discover How Analytics Makes the Difference Between Managing and Improving Performance 2006-11-07 SAS Institute

There is a big difference between formulating a strategy and executing it. Executives set objectives and devise reasonable strategies to achieve them, but more times than not, implementing them proves problematic. An estimated 90 percent of companies fail to fully implement their strategies. Although many contributing factors intervene, such as changing priorities and cultural issues, one consistently recurring flaw is the misapplication or lack of information key to implementing effectual performance management.

The Netrics Difference 2006-08-01 Netrics

Netrics is taking data matching to a whole new level of intelligence--the human level. Conventional computer software is great at exact matching. It can process thousands, even millions, of transactions per second, and achieve an inhuman level of accuracy. But throw in some real-world problems, and that incredibly powerful system can seem pretty helpless. What happens if two digits in the Social Security number are transposed? Or if the customers' first and last names are reversed? Or if the company name is entered slightly differently on two different records?

Read this paper for more information on Netrics' data matching solutions.

Tags: Data Quality, Database Marketing, High Performance Computing, Database Applications, Database Management, Business Intelligence - Data Warehousing

The Design and Analysis of D-optimal Split-Plot Designs Using JMP Version 6 Software 2006-05-01 SAS Institute

An experiment is a process or study that results in the collection of data. The results of experiments are not known in advance. Usually, statistical experiments are conducted when researchers can manipulate the conditions of the experiment and control the factors that are relevant to the research objectives. For example, a rental car company might compare the tread wear of four brands of tires, while controlling the type of car, speed, road surface, weather, and driver. However, there are situations in which a condition is difficult to manipulate. For example, it might be difficult to change the temperature of a furnace from 400º C to 350º C and then back to 400º C.

Using SVM to Extract Acronyms From Text 2006-04-07 Springer Science+Business Media

This paper addresses the problem of extracting acronyms and their expansions from text. The paper proposes a Support Vector Machines (SVM) based approach to deal with the problem. First, all likely acronyms are identified using heuristic rules. Second, expansion candidates are generated from surrounding text of acronyms. Last, SVM model is employed to select the genuine expansions. Analysis shows that the proposed approach has the advantages of saving over the conventional rule based approaches. Experimental results show that the approach outperforms the baseline method of using rules. The paper also shows that the trained SVM model is generic and can adapt to other domains easily.

Tags: Learning Management Systems

Data Mining for Network Intrusion Detection System in Real Time 2006-02-01 Jilin University

Intrusion detection technology is an effective approach to dealing with the problems of network security. This paper present a data mining-based Network Intrusion Detection framework in real time (NIDS). This framework is a distributed architecture consisting of sensor, data preprocessor, extractors of features and detectors. To improve efficiency, the approach adopts a novel FP-tree structure and FP-growth mining method to extract features based on FP-tree without candidate generation. FP-growth is just accord with the system of real-time and updating data frequently as NIDS. It employs DARPA intrusion detection evaluation data set to train and test the feasibility of the proposed method. Experimental results show that the performance is efficient and satisfactory.

Tags: Security Tools, Intrusion Detection Systems

Creation and Deployment of Data Mining-Based Intrusion Detection Systems in Oracle Database 10g 2005-09-30 Oracle

Modern intrusion detection applications face complex requirements - they need to be reliable, extensible, easy to manage, and have low maintenance cost. In recent years, data mining-based Intrusion Detection Systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in the design and implementation of production quality IDSs. Instrumenting components such as data transformations, model deployment, and cooperative distributed detection remain a labor intensive and complex engineering endeavor. This paper describes Database centric Architecture for Intrusion Detection (DAID), a database-centric architecture that leverages data mining within the Oracle RDBMS to address these challenges.

Tags: Intrusion Detection Systems, Database Applications

Empowering Applications With Spatial Analysis and Mining 2005-05-01 Oracle

Oracle Spatial provides new functionality in Oracle Database 10g to analyze, estimate, and predict the influence of the neighborhood based on locations of objects. Such neighborhood information can be visualized using Oracle Application Server MapViewer, or fed into other analysis tools. Alternatively, the neighborhood information can augment existing data used in data mining. This paper describes analysis and mining tasks that can take advantage of the analysis functionality of Oracle Spatial. The paper describes some example applications for performing each of the tasks mentioned in the paper.

Tags: Database Management, Database Applications

Jump to 1 2 [3] 4

Title	Date Added	Company
How Profitable to You Is Each Customer Today... and Tomorrow?: Why Transactional Profitability Measurements Are an Ultimate Goal	2007-03-01	SAS Institute
The problem with accounting's traditional gross profit margin reporting (i.e., restricted to product cost profit margins) is that managers cannot see the bottom half of the total picture - all the profit margin layers eroded from distribution, selling, credit, payments and marketing costs. The unacceptable result from not converting these types of expenses into customer costs is executives, managers and employee teams receive incomplete profit reporting that is not segmented by customer - and the product profitability data they do receive is flawed and misleading. This white paper describes a solution to these deficiencies. It describes a powerful and economical managerial accounting system that collects and transforms data at the detailed transaction level. Tags: Accounting Applications, Business Intelligence - Data Warehousing
Data Mining Techniques for (Network) Intrusion Detection Systems	2007-01-12	University of California
In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Intrusion detection does not, in general, include prevention of intrusions. This paper mostly focused on data mining techniques that are being used for such purposes. It debates on the advantages and disadvantages of these techniques. Finally the paper presents a new idea on how data mining can aid IDSs. Tags: Security Tools, Intrusion Detection Systems
Training Teachers Across a Diversity of Contexts: An Analysis of International Evaluation Data on the Intel Teach Essentials Course, 2006	2007-01-01	Intel
The Intel Education Initiative seeks to form a trusted partnership with ministries of education in countries across the world to support educational reform by integrating technology into project-based learning environments. As part of the partnership, Intel also offers a portfolio of teacher professional development programs. The Intel Education Initiative has consistently invested in the evaluation of the Essentials Course worldwide, both to inform the continuous improvement of the program and its implementation model, and to document and demonstrate the impact of the program on its teacher participants. This report on the global evaluation of the Essentials Course draws on data from both quantitative evaluations done in many countries and qualitative reports that are often part of the local evaluation. Tags: Career Development, Courseware
Discover How Analytics Makes the Difference Between Managing and Improving Performance	2006-11-07	SAS Institute
There is a big difference between formulating a strategy and executing it. Executives set objectives and devise reasonable strategies to achieve them, but more times than not, implementing them proves problematic. An estimated 90 percent of companies fail to fully implement their strategies. Although many contributing factors intervene, such as changing priorities and cultural issues, one consistently recurring flaw is the misapplication or lack of information key to implementing effectual performance management.
The Netrics Difference	2006-08-01	Netrics
Netrics is taking data matching to a whole new level of intelligence--the human level. Conventional computer software is great at exact matching. It can process thousands, even millions, of transactions per second, and achieve an inhuman level of accuracy. But throw in some real-world problems, and that incredibly powerful system can seem pretty helpless. What happens if two digits in the Social Security number are transposed? Or if the customers' first and last names are reversed? Or if the company name is entered slightly differently on two different records? Read this paper for more information on Netrics' data matching solutions. Tags: Data Quality, Database Marketing, High Performance Computing, Database Applications, Database Management, Business Intelligence - Data Warehousing
The Design and Analysis of D-optimal Split-Plot Designs Using JMP Version 6 Software	2006-05-01	SAS Institute
An experiment is a process or study that results in the collection of data. The results of experiments are not known in advance. Usually, statistical experiments are conducted when researchers can manipulate the conditions of the experiment and control the factors that are relevant to the research objectives. For example, a rental car company might compare the tread wear of four brands of tires, while controlling the type of car, speed, road surface, weather, and driver. However, there are situations in which a condition is difficult to manipulate. For example, it might be difficult to change the temperature of a furnace from 400º C to 350º C and then back to 400º C.
Using SVM to Extract Acronyms From Text	2006-04-07	Springer Science+Business Media
This paper addresses the problem of extracting acronyms and their expansions from text. The paper proposes a Support Vector Machines (SVM) based approach to deal with the problem. First, all likely acronyms are identified using heuristic rules. Second, expansion candidates are generated from surrounding text of acronyms. Last, SVM model is employed to select the genuine expansions. Analysis shows that the proposed approach has the advantages of saving over the conventional rule based approaches. Experimental results show that the approach outperforms the baseline method of using rules. The paper also shows that the trained SVM model is generic and can adapt to other domains easily. Tags: Learning Management Systems
Data Mining for Network Intrusion Detection System in Real Time	2006-02-01	Jilin University
Intrusion detection technology is an effective approach to dealing with the problems of network security. This paper present a data mining-based Network Intrusion Detection framework in real time (NIDS). This framework is a distributed architecture consisting of sensor, data preprocessor, extractors of features and detectors. To improve efficiency, the approach adopts a novel FP-tree structure and FP-growth mining method to extract features based on FP-tree without candidate generation. FP-growth is just accord with the system of real-time and updating data frequently as NIDS. It employs DARPA intrusion detection evaluation data set to train and test the feasibility of the proposed method. Experimental results show that the performance is efficient and satisfactory. Tags: Security Tools, Intrusion Detection Systems
Creation and Deployment of Data Mining-Based Intrusion Detection Systems in Oracle Database 10g	2005-09-30	Oracle
Modern intrusion detection applications face complex requirements - they need to be reliable, extensible, easy to manage, and have low maintenance cost. In recent years, data mining-based Intrusion Detection Systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in the design and implementation of production quality IDSs. Instrumenting components such as data transformations, model deployment, and cooperative distributed detection remain a labor intensive and complex engineering endeavor. This paper describes Database centric Architecture for Intrusion Detection (DAID), a database-centric architecture that leverages data mining within the Oracle RDBMS to address these challenges. Tags: Intrusion Detection Systems, Database Applications
Empowering Applications With Spatial Analysis and Mining	2005-05-01	Oracle
Oracle Spatial provides new functionality in Oracle Database 10g to analyze, estimate, and predict the influence of the neighborhood based on locations of objects. Such neighborhood information can be visualized using Oracle Application Server MapViewer, or fed into other analysis tools. Alternatively, the neighborhood information can augment existing data used in data mining. This paper describes analysis and mining tasks that can take advantage of the analysis functionality of Oracle Spatial. The paper describes some example applications for performing each of the tasks mentioned in the paper. Tags: Database Management, Database Applications