[PDF] Top 20 Phrase Clustering for Discriminative Learning
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Phrase Clustering for Discriminative Learning
... word clustering is based on the assumption that words that appear in similar contexts tend to have similar ...distributional clustering of words, we represent the contexts of a phrase as a feature ... See full document
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Phrase Clustering for Smoothing TM Probabilities or, How to Extract Paraphrases from Phrase Tables
... a phrase-based sta- tistical machine translation (SMT) sys- tem, using information in the phrase table ...The clustering is symmetric and recursive: it is applied both to source- language and ... See full document
9
Discriminative Nonnegative Spectral Clustering With Flexible Constrained
... The approach relies on an optimization procedure that includes nullity of the flow from labeled nodes in cluster 1, to labeled nodes in cluster 2. The algorithm closely resembles the semi-supervised harmonic Laplacian ... See full document
6
Verb Phrase Ellipsis Resolution Using Discriminative and Margin Infused Algorithms
... We evaluate our models as usual using precision, re- call and F1 metric for binary classification. The pri- mary results we present in this section are obtained through 5-fold cross validation over all 25 sections of the ... See full document
10
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation
... the phrase “any of” usually stays in front of the subjects (or objects) it ...a discriminative model such as DPR is able to capture various grammatical structures (modelled by phrase movements) ... See full document
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Robust Discriminative Clustering with Sparse Regularizers
... spectral clustering (Ng et ...unsupervised learning algorithms typically have problems identifying the underlying optimal discrete nature of the data; for example, they are quickly perturbed by adding a few ... See full document
50
A Discriminative Learning Model for Coordinate Conjunctions
... We propose a sequence-alignment based method for detecting and disambiguating co- ordinate conjunctions. In this method, av- eraged perceptron learning is used to adapt the substitution matrix to the training data ... See full document
10
Distributed Document and Phrase Co embeddings for Descriptive Clustering
... descriptive clustering task ...descriptive phrase) relies heavily on learning a representation of documents and phrases that can accurately capture relevant semantic ...descriptive clustering ... See full document
11
Discriminative Training of Clustering Functions: Theory and Experiments with Entity Identification
... where clustering approaches are used in order to parti- tion words, determined to be similar, into ...distributional clustering algo- rithm in (Pantel and Lin, 2002), and it shows that func- tionally ... See full document
8
Improved Discriminative ITG Alignment using Hierarchical Phrase Pairs and Semi supervised Training
... these phrase pairs can be ...the phrase alignment space, simultaneously learning translations lexicons for words and phrases without consideration of potentially sub- optimal word alignments and ... See full document
9
Phrase Based Decoding using a Discriminative Model
... a discriminative model (for training a model for Machine Transla- tion), and the standard beam-search based decoding technique (for the translation of an input ...A discriminative ap- proach for ... See full document
9
Discriminative Phrase Embedding for Paraphrase Identification
... We adopt a supervised classification approach to paraphrase identification like most top performing systems. Our focus is representation learning of sen- tences. Following prior work (e.g., Blacoe and Lap- ata ... See full document
6
Multilingual discriminative lexicalized phrase structure parsing
... Nevertheless, free word order languages also tend to be morphologically rich languages. This paper shows that a parsing model that can effec- tively take morphology into account is key for parsing these languages. More ... See full document
10
Discriminative Learning of Syntactic and Semantic Dependencies
... In this paper a discriminative parser is pro- posed to implement maximum entropy (ME) mod- els (Berger, et al., 1996) to address the learning task. The system is divided into two main subsys- tems: ... See full document
5
Discriminative Learning for Joint Template Filling
... Such an approach allows us to learn, for each tar- get relation, an integrated model to weight the dif- ferent extraction options, including for example the likely lengths for events, or the fact that start times should ... See full document
9
The Karlsruhe Institute for Technology Translation System for the ACL WMT 2010
... extracted phrase pairs would be still too ...the phrase extraction stage if one word is aligned to two words which are far away from each other in the ... See full document
5
Discriminative Phrase based Lexicalized Reordering Models using Weighted Reordering Graphs
... in phrase-based statistical ma- chine translation ...in phrase- based models, and finally, all phrases pairs in a sentence pair in the reordering ...all phrase pairs equally and fail to weight the ... See full document
9
Comparative Analysis of EM Clustering Algorithm and Density Based Clustering Algorithm Using WEKA tool.
... unsupervised learning technique is clustering. clustering is organizing data into clusters or groups such that they have high intra-cluster similarity and low inter cluster ...of clustering ... See full document
6
Discriminative Learning of Max-Sum Classifiers
... A discriminative approach is an alternative method which does not require explicit modeling of the underlying probability ...for learning linear ...of learning a linear classifier can be expressed as ... See full document
38
Discriminative Learning Under Covariate Shift
... on learning under sample selection bias has meandered from the statistics and econometrics community into machine learning (Heckman, 1979; Zadrozny, ... See full document
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