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Proceedings of the Fifth SIAM International Conference on Data Mining
The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.
Large-Scale Data Analytics
This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy. There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes sig...
Handbook of Integrated Risk Management for E-Business
“This book provides a recipe for the practical application of technology and is one of the first instances where the tools and technologies that allow for the implementation of solutions to solve specific problems are actually outlined.” --Dr. Krishna Nathan, Vice President, IBM Research This ground-breaking book integrates converging views of e-business processes and offers ways to manage their inherent risks with advanced modeling techniques. Contributors from leading academic and business organizations explore state-of-the-art adaptive risk analysis systems that support business processes in project portfolio management, operations management, supply chain management, inventory contro...
Connectionist-Symbolic Integration
A variety of ideas, approaches, and techniques exist -- in terms of both architecture and learning -- and this abundance seems to lead to many exciting possibilities in terms of theoretical advances and application potentials. Despite the apparent diversity, there is clearly an underlying unifying theme: architectures that bring together symbolic and connectionist models to achieve a synthesis and synergy of the two different paradigms, and the learning and knowledge acquisition methods for developing such architectures. More effort needs to be extended to exploit the possibilities and opportunities in this area. This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic Inte...
Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
Usable Social Science
"Usable Social Science represents a remarkable collaboration between Neil J. Smelser, one of America’s most distinguished sociologists, and John Reed, a highly successful member of corporate America. Together, they accomplish an even more remarkable feat of making accumulated social science knowledge accessible to non-academics while, at the same time, making an academic contribution to the social sciences by reviewing the history, accumulated findings, and conceptual approaches in key areas of specialization in sociology and elsewhere in the social sciences."—Jonathan H. Turner, University Professor & Distinguished Professor of Sociology, University of California, Riverside. “This boo...
Principles of Marketing Engineering, 2nd Edition
The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering-putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). Marketing Engineering is the systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision proces...
Dual Sourcing
Companies with high-performing supply chains enjoy essential competitive ad- vantages. However, supply chain management faces an environment of rising risk that endangers these competitive advantages. One of the reasons is to outsource parts of their business. This bears the risk of significantly increased lead times and lead time variability. It is the impact of lead time variability on inventory management that is the central aspect of this book. It describes a mathematical model for dual sourcing with two reorder points, shows the deviation between stochastic and deterministic calculations in a sensitivity analysis, and investigates different relaxations of a traditional dual-sourcing policy.
Mathematics of Neural Networks
This volume of research papers comprises the proceedings of the first International Conference on Mathematics of Neural Networks and Applications (MANNA), which was held at Lady Margaret Hall, Oxford from July 3rd to 7th, 1995 and attended by 116 people. The meeting was strongly supported and, in addition to a stimulating academic programme, it featured a delightful venue, excellent food and accommo dation, a full social programme and fine weather - all of which made for a very enjoyable week. This was the first meeting with this title and it was run under the auspices of the Universities of Huddersfield and Brighton, with sponsorship from the US Air Force (European Office of Aerospace Resea...
