This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences...

In this book, I’ve tried to maintain a good balance between the basics that every...

Not all features are created equal. This chapter goes over the fundamentals of 3ds Max with an eye toward the most important tools and how you...

As the title of this book suggests, it is an update of the first edition of the Handbook of Natural Language Processing which was edited by Robert Dale, Hermann Moisl, and Harold Somers and published in the year 2000. The vigorous growth of new methods in Natural Language Processing (henceforth, NLP) since then, strongly suggested that...

"Classical and Object-Oriented Software Engineering, 7/E" presents an excellent introduction to software engineering fundamentals, covering both traditional and object-oriented techniques. The coverage of both Agile processes and Open Source Software has been considerably expanded. In addition, the Osbert Oglesby running case study...

As I write this, Java is just beginning its second decade. Unlike many other computer languages whose influence begins to wane over the years, Java’s has grown stronger with the passage of time. Java leapt to the forefront of Internet programming with its first release. Each subsequent version has solidified that position. Today,...

Since the first edition of Semantic Web for the Working Ontologist came out in June 2008, we have been encouraged by the reception the book has received. Practitioners from a wide variety of industries— health care, energy, environmental science, life sciences, national intelligence, and publishing, to name a few—have told...

The Photoshop...

• Master every topic on both new 2011 A+ exams.
• Assess your knowledge and focus your learning.
...

Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of...

Producing on-line, digitized information is no longer a problem. Ever more of our...