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Fast Stochastic ContextFree Parsing: A Stochastic Version of the Valiant Algorithm
 Lecture Notes in Computer Science 4477 (2007) 80–88
"... Abstract. In this work, we present a fast stochastic contextfree parsing algorithm that is based on a stochastic version of the Valiant algorithm. First, the problem of computing the string probability is reduced to a transitive closure problem. Then, the closure problem is reduced to a matrix mult ..."
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Cited by 4 (0 self)
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Abstract. In this work, we present a fast stochastic contextfree parsing algorithm that is based on a stochastic version of the Valiant algorithm. First, the problem of computing the string probability is reduced to a transitive closure problem. Then, the closure problem is reduced to a matrix
Recognition of visual activities and interactions by stochastic parsing
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2000
"... This paper describes a probabilistic syntactic approach to the detection and recognition of temporally extended activities and interactions between multiple agents. The fundamental idea is to divide the recognition problem into two levels. The lower level detections are performed using standard inde ..."
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Cited by 322 (8 self)
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independent probabilistic event detectors to propose candidate detections of lowlevel features. The outputs of these detectors provide the input stream for a stochastic contextfree grammar parsing mechanism. The grammar and parser provide longer range temporal constraints, disambiguate uncertain low
An Efficient ContextFree Parsing Algorithm
, 1970
"... A parsing algorithm which seems to be the most efficient general contextfree algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar topdown algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general; i ..."
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Cited by 798 (0 self)
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A parsing algorithm which seems to be the most efficient general contextfree algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar topdown algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general
Statistical Parsing with a Contextfree Grammar and Word Statistics
, 1997
"... We describe a parsing system based upon a language model for English that is, in turn, based upon assigning probabilities to possible parses for a sentence. This model is used in a parsing system by finding the parse for the sentence with the highest probability. This system outperforms previou ..."
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Cited by 414 (18 self)
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We describe a parsing system based upon a language model for English that is, in turn, based upon assigning probabilities to possible parses for a sentence. This model is used in a parsing system by finding the parse for the sentence with the highest probability. This system outperforms
Three Generative, Lexicalised Models for Statistical Parsing
, 1997
"... In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised contextfree gram mar. We then extend the model to in clude a probabilistic treatment of both subcategorisation and wh~movement. Results on Wall Street Journal text show that the parse ..."
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Cited by 570 (8 self)
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In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised contextfree gram mar. We then extend the model to in clude a probabilistic treatment of both subcategorisation and wh~movement. Results on Wall Street Journal text show
Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora
, 1997
"... ..."
Learning Stochastic Logic Programs
, 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a firstorder r ..."
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Cited by 1194 (81 self)
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Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first
Stochastic Lexicalized ContextFree Grammar
, 1993
"... Stochastic lexicalized contextfree grammar (SLCFG) is an attractive compromise between the parsing efficiency of stochastic contextfree grammar (SCFG) and the lexical sensitivity of stochastic lexicalized treeadjoining grammar (SLTAG). SLCFG is a restricted form of SLTAG that can only generate ..."
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Cited by 43 (6 self)
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Stochastic lexicalized contextfree grammar (SLCFG) is an attractive compromise between the parsing efficiency of stochastic contextfree grammar (SCFG) and the lexical sensitivity of stochastic lexicalized treeadjoining grammar (SLTAG). SLCFG is a restricted form of SLTAG that can only
Querying parse trees of stochastic contextfree grammars
 Proc. 13th International Conference on Database Theory (ICDT), ACM
"... ABSTRACT Stochastic contextfree grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech recognition, information extraction, Webpage wrapping and even analysis of RNA. A string and an SCFG jointly repre ..."
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Cited by 7 (0 self)
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ABSTRACT Stochastic contextfree grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech recognition, information extraction, Webpage wrapping and even analysis of RNA. A string and an SCFG jointly
Probabilistic Parsing in Action Recognition
"... This report addresses the problem of using probabilistic formal languages to describe and understand actions with explicit structure. The paper explores a probabilistic mechanisms of parsing the uncertain input string aided by a stochastic contextfree grammar. This method, originating in speech rec ..."
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Cited by 6 (4 self)
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This report addresses the problem of using probabilistic formal languages to describe and understand actions with explicit structure. The paper explores a probabilistic mechanisms of parsing the uncertain input string aided by a stochastic contextfree grammar. This method, originating in speech
Results 1  10
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63,873