Data mining

Used by corporations, industry, and government to inform and fuel everything from focused advertising to homeland security, data mining can be a very useful tool across a wide range of applications.

Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "e;do-it-yourself"e; approach to extracting interesting patterns from graph data.

Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data.

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging.

Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data.

Cloud computing has created a shift from the use of physical hardware and locally managed software-enabled platforms to that of virtualized cloud-hosted services.

The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers.

Providing a comprehensive review of existing work in music emotion developed in psychology and engineering, this book explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems.

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document.

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects.

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy.

Introduction to Bio-Ontologies explores the computational background of ontologies.

The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews.

This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system.

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity.

This comprehensive volume demonstrates the broad scope of uses for data mining and includes detailed strategies and methodologies for analyzing data from biomedical images, signals, and systems.

In machine learning applications, practitioners must take into account the cost associated with the algorithm.

Explaining how to improve our knowledge-based society, this book addresses problems in collecting, synthesizing, coordinating, and creating knowledge.

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Security and Policy Driven Computing covers recent advances in security, storage, parallelization, and computing as well as applications.

Best-selling author and database expert with more than 25 years of experience modeling application and enterprise data, Dr.

Due to the increasing complexity in application workloads and query engines, database administrators are turning to automated tuning tools that systematically explore the space of physical design alternatives.

An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year.

Similar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality.

This handbook provides a thorough overview of the current state of knowledge in this area.

What do financial data prediction, day-trading rule development, and bio-marker selection have in common?

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts.

Pro Microsoft HDInsight is a complete guide to deploying and using Apache Hadoop on the Microsoft Windows Azure Platforms.

Pro Apache Hadoop, Second Edition brings you up to speed on Hadoop - the framework of big data.

Business intelligence projects do not need to cost multi-millions of dollars or take months or even years to complete!

Foundations of SQL Server 2008 R2 Business Intelligence introduces the entire exciting gamut of business intelligence tools included with SQL Server 2008.

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Every business has reams of business data locked away in databases, business systems, and spreadsheets.

Gaining access to high-quality data is a vital necessity in knowledge-based decision making.

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades.

The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems.

Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field.

Thoroughly covering basic introductions and intuitions, technical details, and formal foundations, this text focuses on the established foundations in this area that have become relatively stable over time.

Due to the advancement of the Internet, online communities are gaining increasing importance in the research community.

Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice.

From basic data mining concepts to state-of-the-art advances, this book covers the theory of the subject as well as its application in a variety of fields.

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research.

As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures.

Thanks to advances in electronic archiving of biodiversity data and the digitization of climate and other geophysical data, a new era in biogeography, functional ecology, and evolutionary ecology has begun.

The emergence of content- and context-aware search engines, which not only personalize searching and delivery but also the content, has caused the emergence of new infrastructures capable of end-to-end ubiquitous transmission of personalized multimedia content to any device on any network at any time.

The First Book to Describe the Technical and Practical Elements of Chemical Text MiningExplores the development of chemical structure extraction capabilities and how to incorporate these technologies in daily research workFor scientific researchers, finding too much information on a subject, not finding enough information, or not being able&nb

After more than 15 years of development drawing on research in cognitive psychology, statistical graphics, computer science, and cartography, micromap designs are becoming part of mainstream statistical visualizations.

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery.

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed.