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362,723
Language trees and zipping.
 PRL,
, 2002
"... In this Letter we present a very general method for extracting information from a generic string of characters, e.g., a text, a DNA sequence, or a time series. Based on datacompression techniques, its key point is the computation of a suitable measure of the remoteness of two bodies of knowledge. ..."
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Cited by 103 (0 self)
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. We present the implementation of the method to linguistic motivated problems, featuring highly accurate results for language recognition, authorship attribution, and language classification. DOI: 10.1103/PhysRevLett.88.048702 PACS numbers: 89.70. +c, 01.20. +x, 05.20. y, 05.45.Tp Many systems
i Language Trees
, 2012
"... Different languages often descend from common ancestor languages from the past. When an original language breaks up into several other languages, it is called a language tree. According to “Ethnologue: Languages of ..."
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Different languages often descend from common ancestor languages from the past. When an original language breaks up into several other languages, it is called a language tree. According to “Ethnologue: Languages of
Semantics of ContextFree Languages
 In Mathematical Systems Theory
, 1968
"... "Meaning " may be assigned to a string in a contextfree language by defining "attributes " of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications of th ..."
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Cited by 568 (0 self)
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"Meaning " may be assigned to a string in a contextfree language by defining "attributes " of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications
On the accuracy of language trees
 PloS ONE
, 2011
"... Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical, phonological, syntactic) features or characters for many different ..."
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Cited by 5 (0 self)
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Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical, phonological, syntactic) features or characters for many
CIL: Intermediate language and tools for analysis and transformation of C programs
 In International Conference on Compiler Construction
, 2002
"... Abstract. This paper describes the CIntermediate Language: a highlevel representation along with a set of tools that permit easy analysis and sourcetosource transformation of C programs. Compared to C, CIL has fewer constructs. It breaks down certain complicated constructs of C into simpler ones, ..."
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Cited by 533 (11 self)
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, and thus it works at a lower level than abstractsyntax trees. But CIL is also more highlevel than typical intermediate languages (e.g., threeaddress code) designed for compilation. As a result, what we have is a representation that makes it easy to analyze and manipulate C programs, and emit them in a
Testing Equivalences for Processes
 Theoretical Computer Science
, 1984
"... Abstract. Given a set of processes and a set of tests on these processes we show how to define in a natural way three different eyuitalences on processes. ThesP equivalences are applied to a particular language CCS. We give associated complete proof systems and fully abstract models. These models ha ..."
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Cited by 526 (37 self)
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Abstract. Given a set of processes and a set of tests on these processes we show how to define in a natural way three different eyuitalences on processes. ThesP equivalences are applied to a particular language CCS. We give associated complete proof systems and fully abstract models. These models
Efficient semantic matching
, 2004
"... We think of Match as an operator which takes two graphlike structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes into prop ..."
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Cited by 854 (68 self)
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We think of Match as an operator which takes two graphlike structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes
Proof verification and hardness of approximation problems
 IN PROC. 33RD ANN. IEEE SYMP. ON FOUND. OF COMP. SCI
, 1992
"... We show that every language in NP has a probablistic verifier that checks membership proofs for it using logarithmic number of random bits and by examining a constant number of bits in the proof. If a string is in the language, then there exists a proof such that the verifier accepts with probabilit ..."
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Cited by 797 (39 self)
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We show that every language in NP has a probablistic verifier that checks membership proofs for it using logarithmic number of random bits and by examining a constant number of bits in the proof. If a string is in the language, then there exists a proof such that the verifier accepts
Symbolic Model Checking for Realtime Systems
 INFORMATION AND COMPUTATION
, 1992
"... We describe finitestate programs over realnumbered time in a guardedcommand language with realvalued clocks or, equivalently, as finite automata with realvalued clocks. Model checking answers the question which states of a realtime program satisfy a branchingtime specification (given in an ..."
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Cited by 576 (50 self)
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We describe finitestate programs over realnumbered time in a guardedcommand language with realvalued clocks or, equivalently, as finite automata with realvalued clocks. Model checking answers the question which states of a realtime program satisfy a branchingtime specification (given
Large margin methods for structured and interdependent output variables
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
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Cited by 623 (12 self)
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the complementary issue of designing classification algorithms that can deal with more complex outputs, such as trees, sequences, or sets. More generally, we consider problems involving multiple dependent output variables, structured output spaces, and classification problems with class attributes. In order
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