Paolo Ferragina – författare

There are many textbooks on algorithms focusing on big-O notation and basic design principles. This book offers a unique approach to taking the design and analyses to the level of predictable practical efficiency, discussing core and classic algorithmic problems that arise in the development of big data applications, and presenting elegant solutions of increasing sophistication and efficiency. Solutions are analyzed within the classic RAM model, and the more practically significant external-memory model that allows one to perform I/O-complexity evaluations. Chapters cover various data types, including integers, strings, trees, and graphs, algorithmic tools such as sampling, sorting, data compression, and searching in dictionaries and texts, and lastly, recent developments regarding compressed data structures. Algorithmic solutions are accompanied by detailed pseudocode and many running examples, thus enriching the toolboxes of students, researchers, and professionals interested in effective and efficient processing of big data.

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.

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.

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.

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).

The papers contained in this volume were presented at the 19th Annual S- posium on Combinatorial Pattern Matching (CPM 2008) held at the University of Pisa, Italy, June 18–20, 2008. All the papers presented at the conference are originalresearchcontributions on computational pattern matching and analysis. They were selected from 78 submissions. Each submission was reviewed by at least three reviewers. The committee decided to accept 25 papers. The programme also includes three invited talks by Daniel M. Gus?eld from the University of California, Davis, USA, J. Ian Munro from the University of Waterloo, Canada, and Prabhakar Raghavan from Yahoo! Research, USA. The objective of the annual CPM meetings is to provide an international forum for research in combinatorial pattern matching and related applications. It addresses issues of searching and matching strings and more complicated p- terns such as trees, regular expressions, graphs, point sets, and arrays. The goal is to derive non-trivialcombinatorialproperties of suchstructures and to exploit these properties in order to either achieve superior performance for the cor- sponding computational problems or pinpoint conditions under which searches cannotbeperformede?ciently. Themeeting also dealswith problems incom- tational biology, data compression, data mining, coding, information retrieval, natural language processing and pattern recognition.