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100   $a20200828d2020      u|         0
101 0 $aeng
135   $aurcn####|||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aString Algorithms in C $eEfficient Text Representation and Search /$fby Thomas Mailund
205   $a1st ed. 2020.
210  1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2020.
215   $a1 online resource (299 pages)
311 08$a9781484259191 
311 08$a148425919X 
320   $aIncludes bibliographical references.
327   $a1. Introduction -- 2. Classical Algorithms for Exact Search -- 3. Suffix Trees -- 4. Suffix Arrays -- 5. Approximate Search -- 6. Conclusions -- Appendix A: Vectors -- Appendix B: Lists -- Appendix C: Queues.
330   $aImplement practical data structures and algorithms for text search and discover how it is used inside other larger applications. This unique in-depth guide explains string algorithms using the C programming language. String Algorithms in C teaches you the following algorithms and how to use them: classical exact search algorithms; tries and compact tries; suffix trees and arrays; approximative pattern searches; and more. In this book, author Thomas Mailund provides a library with all the algorithms and applicable source code that you can use in your own programs. There are implementations of all the algorithms presented in this book so there are plenty of examples. You?ll understand that string algorithms are used in various applications such as image processing, computer vision, text analytics processing from data science to web applications, information retrieval from databases, network security, and much more. You will: Use classical exact search algorithms including naive search, borders/border search, Knuth-Morris-Pratt, and Boyer-Moor with or without Horspool Search in trees, use tries and compact tries, and work with the Aho-Carasick algorithm Process suffix trees including the use and development of McCreight?s algorithm Work with suffix arrays including binary searches; sorting naive constructions; suffix tree construction; skew algorithms; and the Borrows-Wheeler transform (BWT) Deal with enhanced suffix arrays including longest common prefix (LCP) Carry out approximative pattern searches among suffix trees and approximative BWT searches .
606   $aProgramming languages (Electronic computers)
606   $aAlgorithms
606   $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037
606   $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021
606   $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018
615  0$aProgramming languages (Electronic computers)
615  0$aAlgorithms.
615 14$aProgramming Languages, Compilers, Interpreters.
615 24$aAlgorithm Analysis and Problem Complexity.
615 24$aAlgorithms.
676   $a005.1
700   $aMailund$b Thomas$4aut$4http://id.loc.gov/vocabulary/relators/aut$0846442
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906   $aBOOK
912   $a9910416139803321
996   $aString Algorithms in C$92227034
997   $aUNINA