As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.

SIGMOD/PODS'17: International Conference on Management of Data May 14, 2017-May 19, 2017 Chicago, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

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 scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 22nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include algorithms for large-scale private analysis, modelling of entities from social and digital worlds and their relations, querying virtual security views of XML data, recommendation approaches using diversity-based clustering scores, hypothesis discovery, and data aggregation techniques in sensor netwo rk environments.

The forms taken by scientific writing help to determine the very nature of science itself. In this closely reasoned study, Charles Bazerman views the changing forms of scientific writing as solutions to rhetorical problems faced by scientists arguing for their findings. Examining such works as the early Philosophical Transactions and Newton's optical writings as well as Physical Review, Bazerman views the changing forms of scientific writing as solutions to rhetorical problems faced by scientists. The rhetoric of science is, Bazerman demonstrates, an embedded part of scientific activity that interacts with other parts of scientific activity, including social structure and empirical experience. This book presents a comprehensive historical account of the rise and development of the genre, and views these forms in relation to empirical experience.

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 scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 20th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, presents a representative and useful selection of articles covering a wide range of important topics in the domain of advanced techniques for big data management. Big data has become a popular term, used to describe the exponential growth and availability of data. The recent radical expansion and integration of computation, networking, digital devices, and data storage has provided a robust platform for the explosion in big data, as well as being the means by which big data are generated, processed, shared, and analyzed. In general, data are only useful if meaning and value can be extracted from them. Big data discovery enables data scientists and other analysts to uncover patterns and correlations through analysis of large volumes of data of diverse types. Insights gleaned from big data discovery can provide businesses with significant competitive advantages, leading to more successful marketing campaigns, decreased customer churn, and reduced loss from fraud. In practice, the growing demand for large-scale data processing and data analysis applications has spurred the development of novel solutions from both industry and academia.