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The widespread use of XML in business and scientific databases has prompted the development of methodologies, techniques, and systems for effectively managing and analyzing XML data. This has increasingly attracted the attention of different research communities, including database, information retrieval, pattern recognition, and machine learning, from which several proposals have been offered to address problems in XML data management and knowledge discovery. XML Data Mining: Models, Methods, and Applications aims to collect knowledge from experts of database, information retrieval, machine learning, and knowledge management communities in developing models, methods, and systems for XML data mining. This book addresses key issues and challenges in XML data mining, offering insights into the various existing solutions and best practices for modeling, processing, analyzing XML data, and for evaluating performance of XML data mining algorithms and systems.
"This book is a collection of knowledge from experts of database, information retrieval, machine learning, and knowledge management communities in developing models, methods and systems for XML data mining that can be used to address key issues and challenges in XML data mining"--Provided by publisher.
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.
In this book, you will find discussions on the newest native XML databases, along with information on working with XML-enabled relational database systems. In addition, XML Data Management thoroughly examines benchmarks and analysis techniques for performance of XML databases. This book is best used by students that are knowledgeable in database technology and are familiar with XML.
Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.
There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.
"XML for Data Architects" focuses on the combination of architectural and design approaches to using XML, providing numerous syntactical and working examples. It describes the challenges of using XML in a manner that promotes simplification of integration, and a high degree of schema reuse.
Within the last few years Data Warehousing and Knowledge Discovery technology has established itself as a key technology for enterprises that wish to improve the quality of the results obtained from data analysis, decision support, and the automatic extraction of knowledge from data. The Fourth International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2002) continues a series of successful conferences dedicated to this topic. Its main objective is to bring together researchers and practitioners to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. The conference focuses on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covers the most recent and relevant topics in the areas of association rules, clustering, Web mining, security, data mining techniques, data cleansing, applications, data warehouse design and maintenance, and OLAP. These proceedings contain the technical papers selected for presentation at the conference. We received more than 100 papers from over 20 countries, and the program committee finally selected 32 papers. The conference program included one invited talk: “Text Mining Applications of a Shallow Parser” by Walter Daelemans, Univer- ty of Antwerp, Belgium. We would like to thank the DEXA 2002 Workshop General Chair (Roland Wagner) th and the organizing committee of the 13 International Conference on Database and Expert Systems Applications (DEXA 2002) for their support and their cooperation.
Active Media Technology is an area of intelligent information technology and computer science that emphasizes the proactive roles of interfaces and systems. This book brings together papers from researchers from diverse areas, such as Web intelligence, data mining, intelligent agents, smart information use, networking and intelligent interface.
In the great digital era, we are witnessing many rapid scientific and technological developments in human-centered, seamless computing environments, interfaces, devices and systems with applications ranging from business and communication to entertainment and learning. These developments are collectively best characterized as Active Media Technology (AMT), a new area of intelligent information technology and computer science that emphasizes the proactive, seamless roles of interfaces and systems as well as new media in all aspects of digital life. An AMT based computer system offers services that enable the rapid design, implementation, deploying and support of customized solutions. This book brings together papers from researchers from diverse areas, such as Web intelligence, data mining, intelligent agents, smart information use, networking and intelligent interface. The book includes papers on the following topics: Active Computer Systems and Intelligent Interfaces; Adaptive Web Systems and Information Foraging Agents; Web mining, Wisdom Web and Web Intelligence; E-Commerce and Web Services; Data Mining, Ontology Mining and Data Reasoning; Network, Mobile and Wireless Security; Entertainment and Social Applications of Active Media; Agent-Based Software Engineering and Multi-Agent Systems; Digital City and Digital Interactivity; Machine Learning and Human-Centered Robotics; Multi-Modal Processing, Detection, Recognition, and Expression Analysis; Personalized, Pervasive, and Ubiquitous Systems and their Interfaces; Smart Digital Media; and Evaluation of Active Media and AMT Based Systems.