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Data Mining V

Yielding substantial knowledge from data primarily gathered for a wide range of quite different applications, data mining is a promising and relatively new area of current research and development. This book features papers from the Fifth International Conference on Data Mining. Text Mining and Their Business Applications. Sharing state-of-the-art results and practical development experiences, these allow researchers and applications developers from a variety of areas to learn about the many different applications of data mining and how the techniques can help in their own field. The volume features contributions on topics such as: Data Preparation - Data Selection; Preprocessing; Transformation. Techniques - Neural Networks; Decision Trees; Genetic Algorithms; Information Extraction; Clustering; Categorization. Special Applications - Customer Relationship Management; Competitive Intelligence.

Besides, from Web Mining, new research areas were derived to guide the
solutions to its specific needs. In short, some researchers have worked on mining
the content of a web site (web content mining), others have decided to study the ...

Data Mining IV

Illustrating recent advances in data mining problems, encompassing both original research results and practical development experience, this book features the proceedings of the Fourth International Conference of Data Mining, to be held in Rio de Janeiro, Brasil, December 1-3, 2003. Contributions from academia and industry, covering such diverse areas as machine learning, databases, statistics, knowledge acquisitions, data visualization and knowledge-based systems, are included. Data Mining is a promising and relatively new area of current research and development, which can provide important advantages to the user. It can yield substantial knowledge from data primarily gathered for a wide range of quite different applications. Financial institutions have derived considerable benefits from its application and other industries and disciplines are now applying the methodology to increasing effect. The material presented in this book will be of interest to researchers and application developers working in many different areas including statistics, knowledge acquisition, data analysis, IT, data visualization and business and industry.

1.2 Data mining architecture research At the initial stage of data mining process,
most software tools came only with single data mining alogorithm. This kind of
tools requires user master data mining technology and carry out lots of work on ...

Data Mining VIII

Data, Text and Web Mining and Their Business Applications

Information Engineering Management has found applications in many areas, including environmental conservation, economic planning, resource integration, cartography, urban planning, risk assessment, pollution control and transport management systems. Technology plays an active role in the relationship of Data Mining to environmental conservation planning.Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications, this book addresses the new developments in this important field. Featured topics include: Text Mining; Web Content, Structures and Usage Mining; Clustering Technologies; Categorisation Methods; Link Analysis; Data Preparation; Applications in Business, Industry and Government; Applications in Science Engineering; National Security; Customer Relationship Management; Competitive Intelligence; Mining Environment and Geospatial Data; Business Process Management (BPM); Enterprise Information Systems; Applications of GIS and GPS; Applications of MIS; Remote Sensing; Information Systems Strategies and Methodologies and Bio Informatics.

[3] Tan, H., Dillon, T.S., Hadzic, F., Chang, E. and Feng, L. MB3 Miner: mining
eMBedded sub-TREEs using Tree Model Guided candidate generation, In Proc.
of the 1st International Workshop on Mining Complex Data, Houston, Texas, USA
, ...

Data mining VII

data, text, and web mining and their business applications

This book publishes papers from the Seventh International Conference on Data Mining and Information Systems. The book brings together state-of-the-art research results and practical development experiences from researchers and application developers from many different areas. The book covers topics as diverse as: Data Mining Themes such as Text Mining; Web Content, Structure and Usage Mining; Clustering Technologies; Categorisation Methods; Link Analysis; Data Preparation; Applications in Business, Industry and Government; Customer Relationship Management; Competitive Intelligence; Applications in Science and Engineering; Mining Geospatial Data; Business Process Management (BPM); Data Mining Inspired by Nature; National Security, and also Management Information Engineering such as Enterprise Information Systems; Applications of GIS and GPS; Applications of MIS; Remote Sensing; Information Systems Strategies and Methodologies; Hydro and Geo Informatics, Transportation; Bio Informatics; Biodiversity Information Systems.

This book publishes papers from the Seventh International Conference on Data Mining and Information Systems.

Data Mining III

Data Mining brings together techniques from machine learning, pattern recognition, statistics, databases, linguistics and visualization in order to extract information from large databases. Originally principally concerned with behavioural applications, such as the understanding of customer behaviour, its scope has now been widened with the introduction of Text Mining techniques. Areas now encompassed by Data Mining include military, market, and competitive intelligence applications, taxonomies and internet search techniques, and knowledge management applications. Featuring almost 100 contributions from academics and practitioners working around the world, this book contains the proceedings of the Third International Conference on Data Mining.

Featuring almost 100 contributions from academics and practitioners working around the world, this book contains the proceedings of the Third International Conference on Data Mining.

Data Mining X

Data Mining, Protection, Detection and Other Security Technologies

Since the end of the Cold War, the threat of large-scale wars has been substituted by new threats: terrorism, organised crime, trafficking, smuggling, proliferation of weapons of mass destruction. To react to them, a security strategy is necessary, but in order to be effective it requires several instruments, including technological tools. Consequently, research and development in the field of security is proving to be an ever-expanding field all over the world. Data mining is seen more and more not only as a key technology in business, engineering and science but as one of the key features in security. To stress that all these technologies must be seen as a way to improve not only the security of citizens but also their freedom, special attention will be given to data protection research issues. The 10th International Conference on Data Mining is part of the successful series and the topics include: Text mining and text analytics; Data mining applications; Data mining methods.

The 10th International Conference on Data Mining is part of the successful series and the topics include: Text mining and text analytics; Data mining applications; Data mining methods.

Text Mining and Its Applications to Intelligence, CRM and Knowledge Management

Text Mining is an interdisciplinary field bringing together techniques from data mining, linguistics, machine learning, information retrieval, pattern recognition, statistics, databases, and visualization to address the issue of quickly extracting information from large databases. This book has been structured as a self-teaching guide and has been written as a result of the authors' experiences in participating in several large-scale text mining projects.It can be used as a guide for system integrators, and designers of text mining systems, but especially for business analysts and consultants who wish to apply the powerful tools of this technology to real situations. The authors assume readers have little or no previous knowledge about mathematics or linguistics and the book will, therefore, also be a useful resource for graduate students in business and intelligence, and undergraduates in computer science.

This book has been structured as a self-teaching guide and has been written as a result of the authors' experiences in participating in several large-scale text mining projects.It can be used as a guide for system integrators, and designers ...