This second edition of Grune and Jacobs´ brilliant work presents new developments and discoveries that have been made in the field of parsing, or syntax analysis. Parsing has been and continues to be an essential part of computer science and linguistics.
Techniques to retrieve the useful information from web
Enhanced Intrusion Detection System Using Machine Learning Techniques
ANFIS Technique for Identification of Digitally Modulated Signals
A Hybrid Gene Selection Techniques for Cancer Classification
IP Multicast Techniques with Resilient Network Design
This book presents an intuitive picture-oriented approach to the formative processes technique and to its applications. In the first part the authors introduce basic set-theoretic terminology and properties, the decision problem in set theory, and formative processes. The second part of the book is devoted to applications of the technique of formative processes to decision problems. All chapters contain exercises and the book is appropriate for researchers and graduate students in the area of computer science logic. Domenico Cantone is a professor at the Università di Catania. He has been a visiting professor at New York University, Stanford University, ICSI (Berkeley), and Karlsruhe. His interests include mathematical and computer science logic, in particular set theory. Pietro Ursino is a lecturer at the Università dellInsubria, his interests include mathematical logic.
This book offers a comprehensive review of multilabel techniques widely used to classify and label texts, pictures, videos and music in the Internet. A deep review of the specialized literature on the field includes the available software needed to work with this kind of data. It provides the user with the software tools needed to deal with multilabel data, as well as step by step instruction on how to use them. The main topics covered are: •The special characteristics of multi-labeled data and the metrics available to measure them. •The importance of taking advantage of label correlations to improve the results. •The different approaches followed to face multi-label classification. •The preprocessing techniques applicable to multi-label datasets. •The available software tools to work with multi-label data. This book is beneficial for professionals and researchers in a variety of fields because of the wide range of potential applications for multilabel classification. Besides its multiple applications to classify different types of online information, it is also useful in many other areas, such as genomics and biology. No previous knowledge about the subject is required. The book introduces all the needed concepts to understand multilabel data characterization, treatment and evaluation.