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Nowadays, textual databases are among the most rapidly growing
collections of data. Some of these collections contain a new type
of data that differs from classical numerical or textual data.
These are long sequences of symbols, not divided into
well-separated small tokens (words). The most prominent among such
collections are databases of biological sequences, which are
experiencing today an unprecedented growth rate. Starting in 2008,
the "1000 Genomes Project" has been launched with the ultimate goal
of collecting sequences of additional 1,500 Human genomes, 500 each
of European, African, and East Asian origin. This will produce an
extensive catalog of Human genetic variations. The size of just the
raw sequences in this catalog would be about 5 terabytes. Querying
strings without well-separated tokens poses a different set of
challenges, typically addressed by building full-text indexes,
which provide effective structures to index all the substrings of
the given strings. Since full-text indexes occupy more space than
the raw data, it is often necessary to use disk space for their
construction. However, until recently, the construction of
full-text indexes in secondary storage was considered impractical
due to excessive I/O costs. Despite this, algorithms developed in
the last decade demonstrated that efficient external construction
of full-text indexes is indeed possible. This book is about
large-scale construction and usage of full-text indexes. We focus
mainly on suffix trees, and show efficient algorithms that can
convert suffix trees to other kinds of full-text indexes and vice
versa. There are four parts in this book. They are a mix of string
searching theory with the reality of external memory constraints.
The first part introduces general concepts of full-text indexes and
shows the relationships between them. The second part presents the
first series of external-memory construction algorithms that can
handle the construction of full-text indexes for moderately large
strings in the order of few gigabytes. The third part presents
algorithms that scale for very large strings. The final part
examines queries that can be facilitated by disk-resident full-text
indexes. Table of Contents: Structures for Indexing Substrings /
External Construction of Suffix Trees / Scaling Up: When the Input
Exceeds the Main Memory / Queries for Disk-based Indexes /
Conclusions and Open Problems
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Algorithms and Data Structures - 14th International Symposium, WADS 2015, Victoria, BC, Canada, August 5-7, 2015. Proceedings (Paperback, 1st ed. 2015)
Frank Dehne, Joerg-Rudiger Sack, Ulrike Stege
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R3,545
Discovery Miles 35 450
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 14th
Algorithms and Data Structures Symposium, WADS 2015, held in
Victoria, BC, Canada, August 2015. The 54 revised full papers
presented in this volume were carefully reviewed and selected from
148 submissions. The Algorithms and Data Structures Symposium -
WADS (formerly Workshop on Algorithms And Data Structures), which
alternates with the Scandinavian Workshop on Algorithm Theory, is
intended as a forum for researchers in the area of design and
analysis of algorithms and data structures. WADS includes papers
presenting original research on algorithms and data structures in
all areas, including bioinformatics, combinatorics, computational
geometry, databases, graphics, and parallel and distributed
computing.
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