Kategoria BISAC: Computers >> Data Science - Data Analytics

Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business's entire paradigm for a more successful outcome.

Data Mining for Dummies shows you why it doesn't take a...

Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs)....

A hands on guide to web scraping and text mining for both beginners and experienced users of R

• Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL.
• Provides basic techniques to query web documents and data sets (XPath and regular expressions).
• An extensive set of exercises are presented to guide the reader through each technique.
• Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management.
• Case studies...

LogiQL is a new state-of-the-art programming language based on Datalog. It can be used to build applications that combine transactional, analytical, graph, probabilistic, and mathematical programming. LogiQL makes it possible to build hybrid applications that previously required multiple programming languages and databases. In this first book to cover LogiQL, the authors explain how to design, implement, and query deductive databases using this new programming language.

LogiQL s declarative approach enables complex data structures and business rules to be simply specified and then...

By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.
Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry...

"If you have an Oracle Database and want to leverage that data to discover new insights, make predictions, and generate actionable insights, this book is a must read for you In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides you through the basic concepts of data mining and offers step-by-step instructions for solving data-driven problems using SQL...

Linked Data Management presents techniques for querying and managing Linked Data that is available on today s Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.

The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to Linked Data and related standards, including the main principles distinguishing Linked Data from standard database technology. Chapters also describe how to generate links between datasets and explain the overall...

Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of...