Synchronization Algorithms and Concurrent Programming or Mining the Web

Synchronization Algorithms and Concurrent Programming

Author: Gadi Taubenfeld

Synchronization Algorithms and Concurrent Programming

Gadi Taubenfeld

Synchronization is a fundamental challenge in computer science.  It is fast becoming a major performance and design issue for concurrent programming on modern architectures, and for the design of distributed systems.  This is the first text to give a complete and coherent view of all aspects of synchronization algorithms.

Computer science students, programmers, system designers and researchers will be able to solve problems and master techniques that go beyond the treatment provided in introductory texts on operating systems, distributed computing and concurrency.  Dozens of algorithms are presented and their performance is analyzed according to precise complexity measures.

Highlights of the book include

Ø      A wide variety of synchronization problems, algorithms and  key concepts covered in detail.

Ø      Self-review questions with solutions to check your understanding.

Ø      A wealth of end-of-chapter exercises and bibliographic notes.

Ø      Over 300 annotated references guiding you through the contemporary research literature.

Ø      A companion website provides PowerPoint slides and other teaching and learning aids for students and instructors at pearsoned.co.uk/taubenfeld.

 

About the author

Gadi Taubenfeld is an Associate Professor of Computer Science at the Interdisciplinary Center in Herzliya, Israel. He is an established authority in the area of concurrentand distributed computing and has published widely in leading journals and conferences. He was the head of the computer science division at Israel’s Open University; member of technical staff at AT&T Bell Laboratories; consultant to AT&T Labs - Research; and a research scientist and lecturer at Yale University. He holds a PhD in Computer Science from the Technion – Israel Institute of Technology.

New interesting textbook: Cooking for Friends or Taste for Writing

Mining the Web: Discovering Knowledge from Hypertext Data

Author: Soumen Chakrabarti

Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues—including Web crawling and indexing—Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work—painstaking, critical, and forward-looking—readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort.

* A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining.
* Details the special challenges associated with analyzing unstructured and semi-structured data.
* Looks at how classical Information Retrieval techniques have been modified for use with Web data.
* Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning.
* Analyzes current applications for resource discovery and social network analysis.
* An excellent way to introduce students to especially vital applications of data mining and machine learning technology.

Table of Contents:

	Foreword
	Preface
1	Introduction
Pt. I	Infrastructure
2	Crawling the Web
3	Web Search and Information Retrieval
Pt. II	Learning
4	Similarity and Clustering
5	Supervised Learning
6	Semisupervised Learning
Pt. III	Applications
7	Social Network Analysis
8	Resource Discovery
9	The Future of Web Mining
	References
	Index
	About the Author