Edleno S. De Moura, Gonzalo Navarro, Nivio Ziviani et al. · 2007
We present a fast compression and decompression technique for natural language texts. The novelty is that the exact search can be done on the compressed text directly, using any known sequential pattern matching algorithm. Approximate search can also be done efficiently without any decoding. The compression scheme uses a semi-static word-based modelng and a Huffman coding where the coding alphabet is byte-oriented rather than bit-oriented. We use the first bit of each byte to mark the beginning of a word, which allows the searching of the compressed pattern directly on the compressed text. We achieve about 33% compression ratio for typical English texts. When searching for simple patterns, our experiments show that running our algorithm on a compressed text is twice as fast as running agrep on the uncompressed version of the same text. When searching complex or approximate patterns, our algorithm is up to 8 times faster than agrep. 1 Introduction In this paper we present a ...
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Hak, A, Dul, Jan, Mills, A.J. et al. · Data Archiving and Networked Services (DANS) · 2010
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Dávid Pollák · Apress eBooks · 2009
So far, we've explored some of the basic functional cornerstones of Scala: immutable data types and the passing of functions as parameters. The third cornerstone of functional programming is pattern matching. At first glance, pattern matching looks like Java's switch statement. However, pattern matching provides a powerful tool for declaring business logic in a concise and maintainable way. Scala blends traditional functional programming pattern matching with object-oriented concepts to provide a very powerful mechanism for writing programs.KeywordsCase ClassPattern MatchPartial FunctionData HidingScala CodeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Dávid Pollák, Vishal Layka, Andres Sacco · Apress eBooks · 2022
Pattern matching provides a powerful tool for declaring business logic in a concise and maintainable way. Scala blends traditional functional programming pattern matching with object-oriented concepts to provide a very powerful mechanism for writing programs. In this chapter, you’re going to explore the basics of pattern matching. Then you’re going to see how Scala’s case classes bridge object-oriented data encapsulation and function decomposition. Next, you’ll see how Scala’s pattern-matching constructs become functions that can be passed around and composed. Let's look at a simple example first.
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Hak, A., Dul, J. · RePEc: Research Papers in Economics
Pattern matching is comparing two patterns in order to determine whether they match (i.e., that they are the same) or do not match (i.e., that they differ). Pattern matching is the core procedure of theory-testing with cases. Testing consists of matching an “observed pattern” (a pattern of measured values) with an “expected pattern” (a hypothesis), and deciding whether these patterns match (resulting in a confirmation of the hypothesis) or do not match (resulting in a disconfirmation). Essential to pattern matching (as opposed to pattern recognition, which is a procedure by which theory is built) is that the expected pattern is precisely specified before the matching takes place.
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Gonzalo Navarro · 2002
An important subtask of the pattern discovery process is pattern matching, where the pattern sought is already known and we want to determine how often and where it occurs in a sequence.
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Corsi, Cristiana · AMS Campus - AlmaDL · 2016
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W. Brauer, G. Rozenberg, A. Salomaa · Texts in theoretical computer science · 2005
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Roozbeh Hazrat · Springer undergraduate mathematics series · 2015
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Hak, A. (Tony), Dul, J. (Jan) · RePub (Erasmus University Rotterdam) · 2009
Pattern matching is comparing two patterns in order to determine whether they match (i.e., that they are the same) or do not match (i.e., that they differ). Pattern matching is the core procedure of theory-testing with cases. Testing consists of matching an “observed pattern” (a pattern of measured values) with an “expected pattern” (a hypothesis), and deciding whether these patterns match (resulting in a confirmation of the hypothesis) or do not match (resulting in a disconfirmation). Essential to pattern matching (as opposed to pattern recognition, which is a procedure by which theory is built) is that the expected pattern is precisely specified before the matching takes place.
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Joeri Van Eekelen, Sean Leather, Johan Jeuring et al. · 2013
We present a system for program transformation based on the type system of letpolymorphic lambda calculus with fix and case. Transformations are expressed as inference rules and are the input to the transformation system. Transformations are allowed to change the types of terms while the type and transform system ensures type-correctness of the target term. We define both a general transformation system for expressions and patterns that is based on the underlying type system, and give examples of user-defined transformations. Finally, we deal with transforming code to code that uses abstract datatypes, on which we can not pattern match. 1
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Hak, A., Dul, J. · RePEc: Research Papers in Economics
Pattern matching is comparing two patterns in order to determine whether they match (i.e., that they are the same) or do not match (i.e., that they differ). Pattern matching is the core procedure of theory-testing with cases. Testing consists of matching an “observed pattern” (a pattern of measured values) with an “expected pattern” (a hypothesis), and deciding whether these patterns match (resulting in a confirmation of the hypothesis) or do not match (resulting in a disconfirmation). Essential to pattern matching (as opposed to pattern recognition, which is a procedure by which theory is built) is that the expected pattern is precisely specified before the matching takes place.
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Hak, Tony, Dul, Jan · Data Archiving and Networked Services (DANS) · 2009
textabstractPattern matching is comparing two patterns in order to determine whether they match (i.e., that they are the same) or do not match (i.e., that they differ). Pattern matching is the core procedure of theory-testing with cases. Testing consists of matching an “observed pattern” (a pattern of measured values) with an “expected pattern” (a hypothesis), and deciding whether these patterns match (resulting in a confirmation of the hypothesis) or do not match (resulting in a disconfirmation). Essential to pattern matching (as opposed to pattern recognition, which is a procedure by which theory is built) is that the expected pattern is precisely specified before the matching takes place.
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Toby Weston · Apress eBooks · 2017
As well as providing switch-like functionality (that's more powerful than Java's version), pattern matching offers a rich set of "patterns" that can be used to match against. In this chapter, we'll look at the anatomy of patterns and talk through some examples, including literal, constructor, and type query patterns.
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Gonzalo Navarro · Journal of Applied Statistics · 2004
An important subtask of the pattern discovery process is pattern matching, where the pattern sought is already known and we want to determine how often and where it occurs in a sequence. In this paper we review the most practical techniques to find patterns of different kinds. We show how regular expressions can be searched for with general techniques, and how simpler patterns can be dealt with more simply and efficiently. We consider exact as well as approximate pattern matching. Also we cover both sequential searching, where the sequence cannot be preprocessed, and indexed searching, where we have a data structure built over the sequence to speed up the search.
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Dexter Kozen · 1997
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Roozbeh Hazrat · Springer undergraduate mathematics series · 2010
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Sachinrao Jupally, Chalukya Garikapati, Sri Teja et al. · SSRN Electronic Journal · 2023
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Navarro, Gonzalo · Universidad de Chile · 2007
An important subtask of the pattern discovery process is pattern matching, where the pattern sought is already known and we want to determine how often and where it occurs in a sequence. In this paper we review the most practical techniques to find patterns of different kinds. We show how regular expressions can be searched for with general techniques, and how simpler patterns can be dealt with more simply and efficiently. We consider exact as well as approximate pattern matching. Also we cover both sequential searching, where the sequence cannot be preprocessed, and indexed searching, where we have a data structure built over the sequence to speed up the search.
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Bhim P. Upadhyaya · Undergraduate topics in computer science · 2017
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