The focus of the book is on how fundamental statistical and data mining approaches...

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine...

Prediction of Protein Structures, Functions and Interactions presents...

The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would...

Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving...

One familiar problem encountered in association mining exercises is that they...

Although vast activity exists, especially recent, the editors did not find any book that treats applied algorithms in a comprehensive manner. The editors discovered a number of graduate courses in computer science programs with titles such as “Design and Analysis of Algorithms, “Combinatorial Algorithms” “Evolutionary...

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical applications. It is the first book to comprehensively study both approximation algorithms and metaheuristics.

Starting with basic approaches, the...

Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are difficult to solve without advanced computational tools. With the increasing challenges of fulfilling optimization goals of current applications there is a strong drive to advance the development of...

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classification of similar objects into different groups, or more precisely, the partitioning of a data set into subsets...

Progress in biology is dependent on the ability to observe, measure, and model the behavior of organisms at multiple levels of abstraction, from the microscopic to the macroscopic. There has been a tremendous growth recently in the techniques to probe the structure and workings of cellular and organ-level mechanisms. Significant advances have...

This volume of Lecture Notes in Computer Science contains revised versions of papers presented at the 15th International Conference on Implementation and Application of Automata, CIAA 2010. The conference was held at the University of Manitoba in Winnipeg, Canada, on August 12–15, 2010. The previous CIAA conferences were held in London,...