Kategoria BISAC: Computers >> Data Science - Data Analytics

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.
The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different...

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. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science.

The book s introductory part provides context to issues in the astronomical...

This book constitutes the refereed proceedings of the 15th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2016, held in Genova, Italy, in November/December 2016.

The 39 full papers presented were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on optimization and evolutionary algorithms; classification, pattern recognition, and computer vision; multi-agent systems; machine learning; semantic web and description logics; natural language processing; planning and scheduling; and formal...

This book constitutes the refereed conference proceedings of the 10th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2016, held in Chiang Mai, Thailand, in December 2016.

The 22 revised full papers presented together with 5 short papers and 2 abstracts of invited talks were carefully reviewed and selected from 50 submissions. The workshop solicits papers from all areas of AI including cognitive science; computational intelligence; computational philosophy; game theory; machine learning; multi-agent systems; natural language; representation...

This volume contains some lecture notes of the 12th Reasoning Web Summer School (RW 2016), held in Aberdeen, UK, in September 2016.

This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data.

After a general introduction to the business intelligence (BI) process...

Manage your data in a database system designed to support modern application development. The updated edition of this authoritative and accessible guide shows you the many advantages of using document-oriented databases, including how this secure, high-performance system enables flexible data models, high availability, and horizontal scalability.

Written by current and former members of the MongoDB team, the third edition covers new features introduced in MongoDB versions 3.0 and 3.2, and includes a preview of 3.4 features. You'll find substantial updates on querying, indexing,...

The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python's scikit-learn to apply models to text at scale. This practical guide shows programmers and data scientists who have an intermediate-level understanding of Python and a basic understanding of machine learning and natural language processing how to become more proficient in these two exciting areas of data science.

This book presents a concise, focused, and applied approach to text analysis with Python, and covers...

The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them.

Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates...

Principles of research data collection and management is the first practical book written for researchers and research team members covering the do s and don ts about handling data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data.

The first section of the book defines data, introduces fundamental...

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can...

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative data mining techniques, which address the scaling-up of the framework of classical and modern statistical methodology, for predictive modeling and analysis of big data. SM-DM provides proper solutions to common problems facing the newly minted data scientist in the data mining discipline. Its...

This book constitutes the refereed proceedings of the 29th Australasian Joint Conference on Artificial Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016.

The 40 full papers and 18 short papers presented together with 8 invited short papers were carefully reviewed and selected from 121 submissions. The papers are organized in topical sections on agents and multiagent systems; AI applications and innovations; big data; constraint satisfaction, search and optimisation; knowledge representation and reasoning; machine learning and data mining; social intelligence;...

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high...