Results 1 - 10
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13,256
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 context-free 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 ..."
Abstract
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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 context-free 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
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
- In ACL
, 2005
"... Discriminative reranking is one method for constructing high-performance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50-best parses based on a co ..."
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Cited by 522 (15 self)
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Discriminative reranking is one method for constructing high-performance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50-best parses based on a
Statistics for Experimenters
, 2005
"... R factor = 0.052; wR factor = 0.114; data-to-parameter ratio = 18.4. The title compound, [Zn(C8H10F3O2)2(CH4O)2], is a dimethanol coordinated zinc complex with the acetyl acetonate derivative 1,1,1-trifluoro-5,5-dimethylhexane-2,4dionate. The bis--diketonate complex, which is isostructural with its ..."
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Cited by 675 (1 self)
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hydrogen bonds between the methanol hydroxyl groups and neighboring diketonate O atoms create chains running along [100]. Related literature For information regarding the synthesis of various metal-diketonates refer to Watson & Lin (1966). For mass spectrometry related articles see Lerach & Leskiw
Accurate Methods for the Statistics of Surprise and Coincidence
- COMPUTATIONAL LINGUISTICS
, 1993
"... Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used unjustifiably ..."
Abstract
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Cited by 1057 (1 self)
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Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used
An evaluation of statistical approaches to text categorization
- Journal of Information Retrieval
, 1999
"... Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine th ..."
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Cited by 663 (22 self)
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results difficult to interpret and leading to considerable confusions in the literature. Using the results evaluated on the other versions of Reuters which exclude the unlabelled documents, the performance of twelve methods are compared directly or indirectly. For indirect compararions, kNN, LLSF and WORD
A New Statistical Parser Based on Bigram Lexical Dependencies
, 1996
"... This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. Tests using Wall Street Journal ..."
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Cited by 490 (4 self)
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This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. Tests using Wall Street
TnT - A Statistical Part-Of-Speech Tagger
, 2000
"... Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison h ..."
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Cited by 540 (5 self)
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Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison
Thresholding of statistical maps in functional neuroimaging using the false discovery rate.
- NeuroImage
, 2002
"... Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a long-standing problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures for mult ..."
Abstract
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Cited by 521 (9 self)
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for multiple hypothesis testing (e.g., Bonferroni) tend to not be sensitive enough to be useful in this context. This paper introduces to the neuroscience literature statistical procedures for controlling the false discovery rate (FDR). Recent theoretical work in statistics suggests that FDR
Statistical Parsing with a Context-free 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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explain their relative performance. Introduction We present a statistical parser that induces its grammar and probabilities from a hand-parsed corpus (a tree-bank). Parsers induced from corpora are of interest both as simply exercises in machine learning and also because they are often the best parsers
Results 1 - 10
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13,256