G
Gonzalo Navarro
Researcher at University of Chile
Publications - 633
Citations - 24496
Gonzalo Navarro is an academic researcher from University of Chile. The author has contributed to research in topics: Data structure & String searching algorithm. The author has an hindex of 76, co-authored 615 publications receiving 23062 citations. Previous affiliations of Gonzalo Navarro include National University of San Luis & University of Lisbon.
Papers
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A guided tour to approximate string matching
TL;DR: This work surveys the current techniques to cope with the problem of string matching that allows errors, and focuses on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms.
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Searching in metric spaces
TL;DR: A unified view of all the known proposals to organize metric spaces, so as to be able to understand them under a common framework, and presents a quantitative definition of the elusive concept of "intrinsic dimensionality".
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Compressed full-text indexes
Gonzalo Navarro,Veli Mäkinen +1 more
TL;DR: The relationship between text entropy and regularities that show up in index structures and permit compressing them are explained and the most relevant self-indexes are covered, focusing on how they exploit text compressibility to achieve compact structures that can efficiently solve various search problems.
Book
Flexible Pattern Matching in Strings: Practical On-Line Search Algorithms for Texts and Biological Sequences
Gonzalo Navarro,Mathieu Raffinot +1 more
TL;DR: This book presents a practical approach to string matching problems, focusing on the algorithms and implementations that perform best in practice, and includes all of the most significant new developments in complex pattern searching.
Journal ArticleDOI
Compressed representations of sequences and full-text indexes
TL;DR: The FM-index is the first that removes the alphabet-size dependance from all query times and the compressed representation of integer sequences with a compression boosting technique to design compressed full-text indexes that scale well with the size of the input alphabet Σ.