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This book constitutes the refereed proceedings of the 10th International Symposium on String Processing and Information Retrieval, SPIRE 2003, held in Manaus, Brazil, in October 2003. The 21 revised full papers and 6 revised short papers presented together with 2 invited papers were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on Web algorithms, bit-parallel algorithms, compression, categorization and ranking, music retrieval, multilingual information retrieval, subsequences and distributed algorithms, and algorithms on strings and trees.
This book constitutes the joint refereed proceedings of the 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2004 and the 8th International Workshop on Randomization and Computation, RANDOM 2004, held in Cambridge, MA, USA in August 2004. The 37 revised full papers presented were carefully reviewed and selected from 87 submissions. Among the issues addressed are design and analysis of approximation algorithms, inapproximability results, approximation classes, online problems, graph algorithms, cuts, geometric computations, network design and routing, packing and covering, scheduling, game theory, design and analysis of randomised algorithms, randomized complexity theory, pseudorandomness, derandomization, probabilistic proof systems, error-correcting codes, and other applications of approximation and randomness.
The papers contained in this volume were presented at the 13th Annual S- posium on Combinatorial Pattern Matching, held July 3–5, 2002 at the Hotel Uminonakamichi, in Fukuoka, Japan. They were selected from 37 abstracts s- mitted in response to the call for papers. In addition, there were invited lectures by Shinichi Morishita (University of Tokyo) and Hiroki Arimura (Kyushu U- versity). Combinatorial Pattern Matching (CPM) addresses issues of searching and matching strings and more complicated patterns such as trees, regular expr- sions, graphs, point sets, and arrays, in various formats. The goal is to derive n- trivial combinatorial properties of such structures and to exploit these pro...
This volumecontainsthe paperspresented atthe 15thString Processingand - formation Retrieval Symposium (SPIRE), held in Melbourne, Australia, during November 10–12, 2008. The papers presented at the symposium were selected from 54 papers s- mitted in response to the Call For Papers. Each submission was reviewed by a minimum of two, and usually three, Program Committee members, who are expertsdrawnfromaroundthe globe. Thecommittee accepted25papers (46%), with the successful authors also covering a broad rangeof continents. The paper “An E?cient Linear Space Algorithm for Consecutive Su?x Alignment Under Edit Distance” by Heikki Hyyr¨ o was selected for the Best Paper Award, while Dina S...
This book constitutes the refereed proceedings of the 11th International Conference on Language and Automata Theory and Applications, LATA 2017, held in Umeå, Sweden, in March 2017. The 31 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 73 submissions. The papers cover the following topics: algorithmic learning and semantics; automata and logics; combinatorics on words, compression, and pattern matching; complexity; finite automata; grammars, languages, and parsing; graphs and Petri Nets; non-classical automata; and pushdown automata and systems.
This book constitutes the proceedings of the 14th International Computer Science Symposium in Russia, CSR 2019, held in Novosibirsk, Russia, in July 2019. The 31 full papers were carefully reviewed and selected from 71 submissions. The papers cover a wide range of topics such as algorithms and data structures; computational complexity; randomness in computing; approximation algorithms; combinatorial optimization; constraint satisfaction; computational geometry; formal languages and automata; codes and cryptography; combinatorics in computer science; applications of logic to computer science; proof complexity; fundamentals of machine learning; and theoretical aspects of big data.