Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncert
Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social n
Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social n
Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have e
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique
This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is plac
Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, cl
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overvi
"Clustering is a diverse topic, and the underlying algorithms depend greatly on the data domain and problem scenario. This book focuses on three primary aspects of data clustering: the core methods su
