Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.
Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.
Takes a modern approach based on mathematical, probabilistic, and graphical modeling.
Provides an integrated presentation of theory, examples, exercises and applications.
Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web.
Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business, and the social sciences.
"This book is fascinating!" - David Hand (Imperial College, UK)
"This book provides an extremely useful introduction to the intellectually stimulating problems of data mining electronic business." - Andreas S. Weigend (Chief Scientist, Amazon.com)
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Pierre Baldi is a chancellor's professor of computer science at University of California Irvine and the director of its Institute for Genomics and Bioinformatics. Paolo Frasconi is the author of Modeling the Internet and the Web: Probabilistic Methods and Algorithms, published by Wiley.
The World Wide Web is growing in size at a remarkable rate. It is a huge evolving system and its data are rife with uncertainties. Probability and statistics are the fundamental mathematical tools that enable us to model, reason and infer meaningful results from such data. Modelling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the merging properties of the Internet.
Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business and the social sciences.
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