Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter
C.J. Merz, P.M. Murphy. UCI Repository of Machine Learning Databases. Irvine, CA: University of California, Department of Information and Computer Science, http://www.ics.uci.edu/~mlearn/MLOther.html. W. Michalowski, S. Rubin ...
Mukherjee, R., Pati, S.K., Banerjee, A.: Performance tuning of Android applications using clustering and optimization heuristics. In: Advanced data mining tools and methods for social computing (pp.
Mining Imperfect Data: Dealing With Contamination and Incomplete Records. Society ofIndustrial and Applier Mathematics. Project Management Institute (2013). A Guide to the Project Management Body of Knowledge (PMBOKGuides), 5thedn.
Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, ...
P. S. Yu, J. Han, and C. Faloutsos. Link Mining: Models, Algorithms and Applications. New York: Springer, 2010. X. Yin, J. Han, and P. S. Yu. Cross-relational clustering with user's guidance. In Proc. 2005 ACM SIGKDD Int. Conf.
The embedded manufacturing systems are vertically networked with business processes and horizontally connected to disperse ... One-of-a-kind production, changeability, adaptability, modular design, smart industry Introduction Product ...
With a focus on modern techniques as well as past experiences, this vital reference work will be of greatest use to engineers, researchers, and practitioners in scientific-, engineering-, and business-related fields.
Real-World Data Mining demystifies current best practices, showing how to use data mining and analytics to uncover hidden patterns and correlations, and leverage these to improve all business decision-making.
... probit, and related techniques that predict binary or categorical dependent variables, heteroscedasticity has even worse consequences; it biases the regression coefficients as well as their standard errors (R. Williams 2010).
This book provides a simultaneous design blueprint, user guide, and research agenda for current and future developments and will appeal to a broad audience; from developers and users of data mining and grid technology, to advanced ...