Publisher description

Focuses on a few of the important clustering algorithms in the context of information retrieval.

The Multi-dimensional Data Modeling Toolkit represents over 15 years of hands-on experience developing multidimensional analytic applications for over a dozen companies in a variety of application areas. Written in a tutorial style, this book gives, in plain English, a step-by-step development of the defining principles of OLAP analysis through the lens of the programming language at the heart of Oracle's OLAP database option. You will find this book packed with examples, tricks and techniques, concrete illustrations of the programming elements needed to implement. The basics will all be there as well as advanced techniques that you can use to address the most demanding requirements. OLAP will be addressed as an analysis platform. You will learn how to make business intelligence applications smarter by upping the analytical octane. You will learn both the classic applications of OLAP analysis as well as more exotic approaches. You will learn where OLAP fits in among other analytical approaches such as statistics and data mining. So whether you are a developer wanting to learn Oracle's counterpart to Microsoft's MDX, or an analyst wanting to understand the quantitative possibilities of OLAP, The Multi-dimensional Data Modeling Toolkit will show you what you need to know to go from beginner to expert in the application of OLAP analytics with Oracle OLAP DML.

Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.

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.

This book constitutes the refereed proceedings of the 11th International Conference on Database Systems for Advanced Applications, DASFAA 2006, held in Singapore in April 2006. 46 revised full papers and 16 revised short papers presented were carefully reviewed and selected from 188 submissions. Topics include sensor networks, subsequence matching and repeating patterns, spatial-temporal databases, data mining, XML compression and indexing, xpath query evaluation, uncertainty and streams, peer-to-peer and distributed networks and more.

The general theme of MEDICON 2013 is "Research and Development of Technology for Sustainable Healthcare". This decade is being characterized by the appearance and use of emergent technologies under development. This situation has produced a tremendous impact on Medicine and Biology from which it is expected an unparalleled evolution in these disciplines towards novel concept and practices. The consequence will be a significant improvement in health care and well-fare, i.e. the shift from a reactive medicine to a preventive medicine. This shift implies that the citizen will play an important role in the healthcare delivery process, what requires a comprehensive and personalized assistance. In this context, society will meet emerging media, incorporated to all objects, capable of providing a seamless, adaptive, anticipatory, unobtrusive and pervasive assistance. The challenge will be to remove current barriers related to the lack of knowledge required to produce new opportunities for all the society, while new paradigms are created for this inclusive society to be socially and economically sustainable, and respectful with the environment. In this way, these proceedings focus on the convergence of biomedical engineering topics ranging from formalized theory through experimental science and technological development to practical clinical applications.