Data Mining / Analysis - IT Library : ZDNet Asia

White Papers

Case Studies

Vendor Webcast

Show all content

Title Date Added Company

Data-Centric Automated Data Mining 2006-12-14 01:00:24 Oracle

Data mining is a difficult task. It requires complex methodologies, including problem definition, data preparation, model selection, and model evaluation. This has limited the adoption of data mining at large and in the database and Business Intelligence (BI) communities more specifically. The concepts and methodologies used in data mining are foreign to database and BI users in general. This paper proposes a new approach to the design of data mining applications targeted at these user groups. This approach uses a data-centric focus and automated methodologies to make data mining accessible to non-experts. The automated methodologies are exposed through high-level interfaces.

Baby Names, Visualization, and Social Data Analysis 2006-12-09 01:00:18 IBM

The Name Voyager, a web-based visualization of historical trends in baby naming, has proven remarkably popular. This paper discusses the interaction techniques it uses for smooth visual exploration of thousands of time series. It also describes design decisions behind the application and lessons learned in creating an application that makes do-it-oneself data mining popular. The prime lesson, it is hypothesized, is that an information visualization tool may be fruitfully viewed not as a tool but as part of an online social environment. In other words, to design a successful exploratory data analysis tool, one good strategy is to create a system that enables "Social" data analysis.

Semiautomatic Improvements of System-Initiative Spoken Dialog Applications Using Interactive Clustering 2005-11-29 01:00:03 Institute of Electrical and Electronics Engineers

While many successful spoken dialog systems have been deployed over telephone networks, the high cost of developing such applications has led to limited adoption. Despite large research efforts in user-initiative and mixed-initiative systems, most commercial applications follow a system initiative approach because they are simpler to design and are found to work adequately. Yet, even designing such system-initiative spoken dialog systems has proven costly when compared with simpler touchtone systems. To address this issue, this paper describes IEEE's efforts in building diagnostics tools to let non-experienced speech developers write usable applications without the need for transcribing calls.

Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Copartitioning 2005-11-29 01:00:03 Institute of Electrical and Electronics Engineers

Multiclass classification has been investigated for many years in the literature. The scales of real-world multiclass classification applications have become larger and larger. Thus, the scalability of classification methods turns out to be a major concern. To tackle this problem, hierarchical classification is proposed and widely adopted to get better trade-off between effectiveness and efficiency. A novel algorithm to automatically mine a hierarchical structure from the flat taxonomy of a data corpus as a preparation for the adoption of hierarchical classification is proposed in this paper.

Adding Data Mining to Extend Your OLAP BI Solution: The Cube Factory 2006-03-03 01:01:29 Oracle

To design and manage a large dimensional model can be a challenge. In an ideal world users would design their query and build their own dimensional models at run time. The problem with this ideal world is, in the context of large 'n' dimensional model, how do users know which dimensions, or attributes, are important in the context of their specific analysis? Oracle's gold-standard 10g database engine provides the ability to perform multidimensional, relational and data mining operations all within the same integrated engine. This paper will explain how to use the Oracle BI10g Solution to exploit the new capabilities provided by OLAP and data mining analytic features.

Oracle Data Mining 10g Release 2: Know More, Do More, Spend Less 2006-12-22 01:00:22 Oracle

Oracle Data Mining is powerful data mining software embedded in the Oracle Database that enables to discover new insights hidden in the data. Oracle Data Mining helps businesses to target their best customers, find and prevent fraud, discover the most influential attributes that affect Key Performance Indicators (KPIs), and find valuable new information hidden in the data. Oracle Data Mining helps technical professionals find patterns in their data, identify key attributes, discover new clusters and associations, and uncover valuable insights. With Oracle Data Mining, everything occurs in the Oracle Database - in a single, secure, scalable, platform for business intelligence. Oracle Data Mining represents a breakthrough in business intelligence. Oracle Data Mining moves the analytical.

Using Rational Unified Process in an SME - A Case Study 2006-04-25 04:24:21

The Rational Unified Process (RUP) is a comprehensive software development process framework emphasizing use-cases, architecture focus and an iterative approach. RUP is widely known and many organizations have tried to adopt it. Being a framework, RUP has to, in some way, be tailored to the specific context of use, no software development project is alike. This paper presents a case study of a Norwegian SME that tried to adopt RUP in the simplest way, by introducing the methodology by providing comprehensive documentation and some simple training. This study shows that the use of RUP had some positive effects but also that the use has been scattered.

Shared Display Wall Based Collaboration Environment in the Control Room of the DIII-D National Fusion Facility 2006-09-08 01:00:28 Princeton University

At the DIII-D National Fusion Facility control room, a large format shared display is being used in the control room to support routine collaborative scientific investigation during experimental operations. The US National Fusion Collaboratory Project conducted an observational study in order to identify the best ways of utilizing the shared display wall for control room collaborations. The findings of the study motivated the deployment of shared display-based software tools in three categories: visualization tools that provide up-to-date information about experiment status and group activity, data analysis sharing tools that enable researchers to move the information from personal desktop screens into the large shared display wall, advanced remote participation and video conferencing tools that present the life-size video of remotely participating core team members.

Serving Georgia's Citizens Through Effective G-to-G Collaboration 2005-08-30 03:00:02

The delivery of health and human services (HHS) to Georgia's residents is frequently hindered by disparate information systems, counter-intuitive processes, and the bureaucratic culture of the state's various agencies. HHS employees often must enter client data multiple times, into multiple information systems - depending upon the data needs of the county, city, or state. As is true in many states, citizens find themselves confounded by government processes that rarely offer intuitive, effective access to critically needed services.

Email Data Cleaning 2006-05-02 03:56:23 Association for Computing Machinery

Addressed in this paper is the issue of 'Email data cleaning' for text mining. Email data is usually noisy and thus it is necessary to clean it before mining. Several products offer email cleaning features, however, the types of noises that can be eliminated are restricted. A thorough and systematic investigation on the issue is thus needed. In this paper, email cleaning is formalized as a problem of non-text filtering and text normalization. In this way, email cleaning becomes independent from any specific text mining processing. A cascaded approach is proposed, which cleans up an email in four passes including non-text filtering, paragraph normalization, sentence normalization, and word normalization.

Jump to 1 2 3 4 5 6 7 8 [9] 10

Data Management

Related TechGuides

Featured Whitepapers

Webcast:

Enabling Telecom 2.0 with the next generation Service Delivery Platform

Featured Speakers

Oracle Technology Solutions for Midsize Businesses

Industry Report: Financial Services

Title	Date Added	Company
Data-Centric Automated Data Mining	2006-12-14 01:00:24	Oracle
Data mining is a difficult task. It requires complex methodologies, including problem definition, data preparation, model selection, and model evaluation. This has limited the adoption of data mining at large and in the database and Business Intelligence (BI) communities more specifically. The concepts and methodologies used in data mining are foreign to database and BI users in general. This paper proposes a new approach to the design of data mining applications targeted at these user groups. This approach uses a data-centric focus and automated methodologies to make data mining accessible to non-experts. The automated methodologies are exposed through high-level interfaces.
Baby Names, Visualization, and Social Data Analysis	2006-12-09 01:00:18	IBM
The Name Voyager, a web-based visualization of historical trends in baby naming, has proven remarkably popular. This paper discusses the interaction techniques it uses for smooth visual exploration of thousands of time series. It also describes design decisions behind the application and lessons learned in creating an application that makes do-it-oneself data mining popular. The prime lesson, it is hypothesized, is that an information visualization tool may be fruitfully viewed not as a tool but as part of an online social environment. In other words, to design a successful exploratory data analysis tool, one good strategy is to create a system that enables "Social" data analysis.
Semiautomatic Improvements of System-Initiative Spoken Dialog Applications Using Interactive Clustering	2005-11-29 01:00:03	Institute of Electrical and Electronics Engineers
While many successful spoken dialog systems have been deployed over telephone networks, the high cost of developing such applications has led to limited adoption. Despite large research efforts in user-initiative and mixed-initiative systems, most commercial applications follow a system initiative approach because they are simpler to design and are found to work adequately. Yet, even designing such system-initiative spoken dialog systems has proven costly when compared with simpler touchtone systems. To address this issue, this paper describes IEEE's efforts in building diagnostics tools to let non-experienced speech developers write usable applications without the need for transcribing calls.
Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Copartitioning	2005-11-29 01:00:03	Institute of Electrical and Electronics Engineers
Multiclass classification has been investigated for many years in the literature. The scales of real-world multiclass classification applications have become larger and larger. Thus, the scalability of classification methods turns out to be a major concern. To tackle this problem, hierarchical classification is proposed and widely adopted to get better trade-off between effectiveness and efficiency. A novel algorithm to automatically mine a hierarchical structure from the flat taxonomy of a data corpus as a preparation for the adoption of hierarchical classification is proposed in this paper.
Adding Data Mining to Extend Your OLAP BI Solution: The Cube Factory	2006-03-03 01:01:29	Oracle
To design and manage a large dimensional model can be a challenge. In an ideal world users would design their query and build their own dimensional models at run time. The problem with this ideal world is, in the context of large 'n' dimensional model, how do users know which dimensions, or attributes, are important in the context of their specific analysis? Oracle's gold-standard 10g database engine provides the ability to perform multidimensional, relational and data mining operations all within the same integrated engine. This paper will explain how to use the Oracle BI10g Solution to exploit the new capabilities provided by OLAP and data mining analytic features.
Oracle Data Mining 10g Release 2: Know More, Do More, Spend Less	2006-12-22 01:00:22	Oracle
Oracle Data Mining is powerful data mining software embedded in the Oracle Database that enables to discover new insights hidden in the data. Oracle Data Mining helps businesses to target their best customers, find and prevent fraud, discover the most influential attributes that affect Key Performance Indicators (KPIs), and find valuable new information hidden in the data. Oracle Data Mining helps technical professionals find patterns in their data, identify key attributes, discover new clusters and associations, and uncover valuable insights. With Oracle Data Mining, everything occurs in the Oracle Database - in a single, secure, scalable, platform for business intelligence. Oracle Data Mining represents a breakthrough in business intelligence. Oracle Data Mining moves the analytical.
Using Rational Unified Process in an SME - A Case Study	2006-04-25 04:24:21
The Rational Unified Process (RUP) is a comprehensive software development process framework emphasizing use-cases, architecture focus and an iterative approach. RUP is widely known and many organizations have tried to adopt it. Being a framework, RUP has to, in some way, be tailored to the specific context of use, no software development project is alike. This paper presents a case study of a Norwegian SME that tried to adopt RUP in the simplest way, by introducing the methodology by providing comprehensive documentation and some simple training. This study shows that the use of RUP had some positive effects but also that the use has been scattered.
Shared Display Wall Based Collaboration Environment in the Control Room of the DIII-D National Fusion Facility	2006-09-08 01:00:28	Princeton University
At the DIII-D National Fusion Facility control room, a large format shared display is being used in the control room to support routine collaborative scientific investigation during experimental operations. The US National Fusion Collaboratory Project conducted an observational study in order to identify the best ways of utilizing the shared display wall for control room collaborations. The findings of the study motivated the deployment of shared display-based software tools in three categories: visualization tools that provide up-to-date information about experiment status and group activity, data analysis sharing tools that enable researchers to move the information from personal desktop screens into the large shared display wall, advanced remote participation and video conferencing tools that present the life-size video of remotely participating core team members.
Serving Georgia's Citizens Through Effective G-to-G Collaboration	2005-08-30 03:00:02
The delivery of health and human services (HHS) to Georgia's residents is frequently hindered by disparate information systems, counter-intuitive processes, and the bureaucratic culture of the state's various agencies. HHS employees often must enter client data multiple times, into multiple information systems - depending upon the data needs of the county, city, or state. As is true in many states, citizens find themselves confounded by government processes that rarely offer intuitive, effective access to critically needed services.
Email Data Cleaning	2006-05-02 03:56:23	Association for Computing Machinery
Addressed in this paper is the issue of 'Email data cleaning' for text mining. Email data is usually noisy and thus it is necessary to clean it before mining. Several products offer email cleaning features, however, the types of noises that can be eliminated are restricted. A thorough and systematic investigation on the issue is thus needed. In this paper, email cleaning is formalized as a problem of non-text filtering and text normalization. In this way, email cleaning becomes independent from any specific text mining processing. A cascaded approach is proposed, which cleans up an email in four passes including non-text filtering, paragraph normalization, sentence normalization, and word normalization.