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Suffix Array
In computer science, a suffix array is a sorted array of all suffixes of a string. It is a data structure used in, among others, full-text indices, data-compression algorithms, and the field of bibliometrics. Suffix arrays were introduced by as a simple, space efficient alternative to suffix trees. They had independently been discovered by Gaston Gonnet in 1987 under the name ''PAT array'' . gave the first in-place \mathcal(n) time suffix array construction algorithm that is optimal both in time and space, where ''in-place'' means that the algorithm only needs \mathcal(1) additional space beyond the input string and the output suffix array. Enhanced suffix arrays (ESAs) are suffix arrays with additional tables that reproduce the full functionality of suffix trees preserving the same time and memory complexity. A sorted array of only some (rather than all) suffixes of a string is called a sparse suffix array. Definition Let S=S ..S /math> be an n-string and let S ,j/math ...
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List Of Data Structures
This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures. Data types Primitive types * Boolean, true or false. * Character *Floating-point representation of a finite subset of the rationals. ** Including single-precision and double-precision IEEE 754 floats, among others * Fixed-point representation of the rationals *Integer, a direct representation of either the integers or the non-negative integers *Reference, sometimes erroneously referred to as a pointer or handle, is a value that refers to another value, possibly including itself *Symbol, a unique identifier *Enumerated type, a set of symbols *Complex, representation of complex numbers Composite types or non-primitive type * Array, a sequence of elements of the same type stored contiguously in memory * Record (also called a structure or ...
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FM-index
In computer science, an FM-index is a compressed full-text substring index based on the Burrows–Wheeler transform, with some similarities to the suffix array. It was created by Paolo Ferragina and Giovanni Manzini,Paolo Ferragina and Giovanni Manzini (2000)"Opportunistic Data Structures with Applications".Proceedings of the 41st Annual Symposium on Foundations of Computer Science. p.390. who describe it as an opportunistic data structure as it allows compression of the input text while still permitting fast substring queries. The name stands for Full-text index in Minute space. It can be used to efficiently find the number of occurrences of a pattern within the compressed text, as well as locate the position of each occurrence. The query time, as well as the required storage space, has a sublinear complexity with respect to the size of the input data. The original authors have devised improvements to their original approach and dubbed it "FM-Index version 2". A further improvem ...
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Articles With Example Python (programming Language) Code
Article often refers to: * Article (grammar), a grammatical element used to indicate definiteness or indefiniteness * Article (publishing), a piece of nonfictional prose that is an independent part of a publication Article(s) may also refer to: Government and law * Elements of treaties of the European Union * Articles of association, the regulations governing a company, used in India, the UK and other countries; called articles of incorporation in the US * Articles of clerkship, the contract accepted to become an articled clerk * Articles of Confederation, the predecessor to the current United States Constitution * Article of impeachment, a formal document and charge used for impeachment in the United States * Article of manufacture, in the United States patent law, a category of things that may be patented * Articles of organization, for limited liability organizations, a US equivalent of articles of association Other uses * Article element , in HTML * "Articles", a song ...
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Lecture Notes In Computer Science
''Lecture Notes in Computer Science'' is a series of computer science books published by Springer Science+Business Media since 1973. Overview The series contains proceedings, post-proceedings, monographs, and Festschrifts. In addition, tutorials, state-of-the-art surveys, and "hot topics" are increasingly being included. The series is indexed by DBLP. See also *'' Monographiae Biologicae'', another monograph series published by Springer Science+Business Media *'' Lecture Notes in Physics'' *'' Lecture Notes in Mathematics'' *'' Electronic Workshops in Computing'', published by the British Computer Society image:Maurice Vincent Wilkes 1980 (3).jpg, Sir Maurice Wilkes served as the first President of BCS in 1957. The British Computer Society (BCS), branded BCS, The Chartered Institute for IT, since 2009, is a professional body and a learned ... References External links * Academic journals established in 1973 Computer science books Series of non-fiction books ...
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Statistical Machine Translation
Statistical machine translation (SMT) is a machine translation approach where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation, that superseded the previous rule-based approach that required explicit description of each and every linguistic rule, which was costly, and which often did not generalize to other languages. The first ideas of statistical machine translation were introduced by Warren Weaver in 1949, including the ideas of applying Claude Shannon's information theory. Statistical machine translation was re-introduced in the late 1980s and early 1990s by researchers at IBM's Thomas J. Watson Research Center. Before the introduction of neural machine translation, it was by far the most widely studied machine translation method. Basis The idea b ...
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Phrase Table
In grammar, a phrasecalled expression in some contextsis a group of words or singular word acting as a grammatical unit. For instance, the English expression "the very happy squirrel" is a noun phrase which contains the adjective phrase "very happy". Phrases can consist of a single word or a complete sentence. In theoretical linguistics, phrases are often analyzed as units of syntactic structure such as a constituent. There is a difference between the common use of the term ''phrase'' and its technical use in linguistics. In common usage, a phrase is usually a group of words with some special idiomatic meaning or other significance, such as " all rights reserved", "economical with the truth", " kick the bucket", and the like. It may be a euphemism, a saying or proverb, a fixed expression, a figure of speech, etc.. In linguistics, these are known as phrasemes. In theories of syntax, a phrase is any group of words, or sometimes a single word, which plays a particular role within ...
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Example-based Machine Translation
Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning. Translation by analogy At the foundation of example-based machine translation is the idea of translation by analogy. When applied to the process of human translation, the idea that translation takes place by analogy is a rejection of the idea that people translate sentences by doing deep linguistic analysis. Instead, it is founded on the belief that people translate by first decomposing a sentence into certain phrases, then by translating these phrases, and finally by properly composing these fragments into one long sentence. Phrasal translations are translated by analogy to previous translations. The principle of translation by analogy is encoded to example-b ...
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Binary Search
In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search algorithm that finds the position of a target value within a sorted array. Binary search compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the remaining half, again taking the middle element to compare to the target value, and repeating this until the target value is found. If the search ends with the remaining half being empty, the target is not in the array. Binary search runs in Time complexity#Logarithmic time, logarithmic time in the Best, worst and average case, worst case, making O(\log n) comparisons, where n is the number of elements in the array. Binary search is faster than linear search except for small arrays. However, the array must be sorted first to be able to apply binary search. There are specialized data structures designed fo ...
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Index (search Engine)
Search engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. An alternate name for the process, in the context of search engines designed to find web pages on the Internet, is '' web indexing''. Popular search engines focus on the full-text indexing of online, natural language documents. Media types such as pictures, video, audio, and graphics are also searchable. Meta search engines reuse the indices of other services and do not store a local index whereas cache-based search engines permanently store the index along with the corpus. Unlike full-text indices, partial-text services restrict the depth indexed to reduce index size. Larger services typically perform indexing at a predetermined time interval due to the required time and processing costs, while agent-based search ...
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Silesia Corpus
The Silesia corpus is a collection of files intended for use as a benchmark for testing lossless data compression algorithms. It was created in 2003 as an alternative for the Canterbury corpus and Calgary corpus, based on concerns about how well these represented modern files. It contains various data types, including large text documents, executable files, and databases. Contents The corpus consists of 12 files, totaling 211MB. The files were chosen to represent what the author considered to be data types likely to grow rapidly in size over time, such as computer programs and databases, along with more traditional compression benchmarks, such as large text files. Because it has a broader and more modern selection of datatypes, it is considered a better source of test data for compression algorithms when compared to the Calgary corpus. See also * Data compression In information theory, data compression, source coding, or bit-rate reduction is the process of encoding in ...
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Open Source
Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use and view the source code, design documents, or content of the product. The open source model is a decentralized software development model that encourages open collaboration. A main principle of Open-source software, open source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open source appropriate technology, and open source drug discovery. Open source promotes universal access via an open-source or free license to a product's design or blueprint, and universal redistribution of that design or blueprint. Before the phrase ''open source'' became widely adopted, developers and producers used a variety of other terms, suc ...
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External Memory Algorithm
In computing, external memory algorithms or out-of-core algorithms are algorithms that are designed to process data that are too large to fit into a computer's main memory at once. Such algorithms must be optimized to efficiently fetch and access data stored in slow bulk memory (auxiliary memory) such as hard drives or tape drives, or when memory is on a computer network. External memory algorithms are analyzed in the external memory model. Model External memory algorithms are analyzed in an idealized model of computation called the external memory model (or I/O model, or disk access model). The external memory model is an abstract machine similar to the RAM model, RAM machine model, but with a Cache (computing), cache in addition to main memory. The model captures the fact that read and write operations are much faster in a cache (computing), cache than in main memory, and that Reading (computer), reading long contiguous blocks is faster than reading randomly using a disk read-a ...
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