Learn IT - Books tags mining

Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data

Apress, 2015

A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can...

Data Mining: Concepts, Models and Techniques (Intelligent Systems Reference Library)

Springer, 2011

Data Mining represents a complex of technologies that are rooted in many disciplines: mathematics, statistics, computer science, physics, engineering, biology, etc., and with diverse applications in a large variety of different domains: business, health care, science and engineering, etc. Basically, data mining can be seen as the science of...

Text Mining: Classification, Clustering, and Applications

CRC Press, 2009

This book is a worthy contribution to the field of text mining. By focusing on classification (rather than exhaustively covering extraction, summarization, and other tasks), it achieves the right balance of coherence and comprehensiveness. It collects papers by the leading authors in the field, who employ and explain a variety of...

Handbook of Educational Data Mining (CRC Data Mining and Knowledge Discovery Series)

CRC Press, 2010

The goal of this book is to provide an overview of the current state of knowledge of educational data mining (EDM). The primary goal of EDM is to use large-scale educational data sets to better understand learning and to provide information about the learning process. Although researchers have been studying human learning for over a...

Handbook of Research on Text and Web Mining Technologies

Information Science Publishing, 2008

The massive daily overflow of electronic data to information seekers creates the need for better ways to digest and organize this information to make it understandable and useful. Text mining, a variation of data mining, extracts desired information from large, unstructured text collections stored in electronic forms.

The...

Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)

Springer, 2004

This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications....

Handbook of Natural Language Processing, Second Edition

CRC Press, 2010

As the title of this book suggests, it is an update of the first edition of the Handbook of Natural Language Processing which was edited by Robert Dale, Hermann Moisl, and Harold Somers and published in the year 2000. The vigorous growth of new methods in Natural Language Processing (henceforth, NLP) since then, strongly suggested that...

Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)

Springer, 2002

Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source...

The Influence of Technology on Social Network Analysis and Mining (Lecture Notes in Social Networks)

Springer, 2013

The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant...

Clinical Data-Mining: Integrating Practice and Research (Pocket Guides to Social Work Research Methods)

Oxford University Press, 2009

Clinical Data-Mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practice knowledge-building, clinical decision-making and practitioner reflection. Depending upon the type of data mined, CDM can be qualitative or quantitative; it is generally retrospective, but may be...

Understanding Complex Datasets: Data Mining with Matrix Decompositions

CRC Press, 2007

Many data-mining algorithms were developed for the world of business, for example for customer relationship management. The datasets in this environment, although large, are simple in the sense that a customer either did or did not buy three widgets, or did or did not fly from Chicago to Albuquerque.

In contrast,...

Unsupervised Learning with R

Packt Publishing, 2015

Work with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data

About This Book

Unlock and discover how to tackle clusters of raw data through practical examples in R

Explore your data and create your own models from scratch

...

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