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On the Construction and Application of Compressed Text Indexes

On the Construction and Application of Compressed Text Indexes


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About the Book

This dissertation, "On the Construction and Application of Compressed Text Indexes" by Wing-kai, Hon, 韓永楷, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled \On the Construction and Application of Compressed Text Indexes" submitted by Hon Wing Kai for the degree of Doctor of Philosophy at the University of Hong Kong in August 2004 Text indexing involves the preprocessing of a text to build a data structure which enables ecient matching of this text against any pattern afterwards. Tra- ditional indexes like sux trees and sux arrays oer superb matching perfor- mance in theory, and have found numerous applications in practice. However, they consume a lot of space. For a text of lengthn, they have a space requirement of O(n logn) bits, and this demanding space requirement has limited their use for indexing long texts such as DNA sequences. Recent developments, notably the Compressed Sux Arrays (CSA) of Grossi and Vitter, and the FM-index of Ferragina and Manzini, have oered hope of reducing the space requirements of traditional indexes. These two indexes re- quire space linear to the number of bits of the original text, and the matching performance is only slowed down by a polylog(n) factor. However, for such an index to be useful, it must have a space-ecient construction. In this study, we improve an existing construction algorithm for the CSA, and show that the CSA and FM-index can be constructed in O(n logn) time using optimal space. We also provide another construction algorithm, which runs in optimal time and optimal space when the text is over a constant-size alphabet. We also give a space-ecient construction algorithm for the Compressed Sux Tree (CST) of Sadakane. This data structure, together with the CSA and the FM-index, can help to solve other advanced text matching problems. Firstly, we show that the CST alone can be used to nd the maximal unique matches, the core problem of a real application in computational biology. We then use the CSA, FM-index and CST to design the rst two compressed indexes of size O(d logjj) bits for managing a collection of texts of total length d, which allow insertion or deletion of text in the collection, and respectively support the classical dictionary matching and library matching queries. Our query and update times are only within a factor of polylog(d) from the best results from previous studies that require (d logd) bits. Interestingly, these two indexes can work together toii manage a dynamic text that supports ecient pattern matching, while allowing insertion or deletion of substring at arbitrary position. Finally, we study the practical aspects of CSA and FM-index. In particular, we successfully implement both data structures for the human genome (2:8810 characters) and other DNA sequences on an ordinary PC with 4 Gbyte RAM. We also compare the matching performance of these two data structures, and obtain some counter-intuitive ndings. DOI: 10.5353/th_b3105973 Subjects: Text processing (Computer science)Automatic indexingData structures (Computer science)Pattern recognition systems


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Product Details
  • ISBN-13: 9781374727571
  • Publisher: Open Dissertation Press
  • Publisher Imprint: Open Dissertation Press
  • Height: 279 mm
  • Weight: 254 gr
  • ISBN-10: 1374727571
  • Publisher Date: 27 Jan 2017
  • Binding: Paperback
  • Spine Width: 5 mm
  • Width: 216 mm


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