Bøger af Paolo Ferragina

"This book provides students, researchers and professionals working in big data applications with solutions to core algorithmic problems, analyzed within RAM and external-memory models of computation. Pseudocode and running examples deal with various data types, and algorithmic tools for sampling, sorting, search, and data compression are included"--

This volume contains the papers presented at the 13th International Symposium on String Processing and Information Retrieval (SPIRE), held October 11-13, 2006, in Glasgow, Scotland. The SPIRE annual symposium provides an opportunity for both new and established researchers to present original contributions to areas such as string processing (dictionary algorithms, text searching, pattern matching, text c- pression, text mining, natural language processing, and automata-based string processing); information retrieval languages, applications, and evaluation (IR modelling, indexing, ranking and ?ltering, interface design, visualization, cro- lingual IR systems, multimedia IR, digital libraries, collaborative retrieval, W- related applications, XML, information retrieval from semi-structured data, text mining, and generation of structured data from text); and interaction of biology and computation (sequencing and applications in molecular biology, evolution and phylogenetics, recognition of genes and regulatory elements, and sequen- driven protein structure prediction). The papers in this volume were selected from 102 papers submitted from over 20 di?erent countries in response to the Call for Papers. A total of 26 submissions were accepted as full papers, yielding an acceptance rate of about 25%. In view of the large number of good-quality submissions the Program Committee decided to accept 5 short papers, that have also been included in the proceedings. SPIRE 2006 also featured two talks by invited speakers: Jamie Callan (Carnegie Mellon University, USA) and Martin Farach-Colton (Rutgers University, USA).

This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finance, cryptography, Web search, and data compression.The book is suitable for undergraduate students in computer science, engineering, and applied mathematics, university students in other fields, high-school students with an interest in STEM subjects, and professionals who want an insight into algorithmic solutions and the related mindset. While the authors assume only basic mathematical knowledge, they uphold the scientific rigor that is indispensable for transforming general ideas into executable algorithms. A supporting website contains examples and Python code for implementing the algorithms in the book.