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Báo cáo khoa học: "An Unsupervised Model for Statistically Determining Coordinate Phrase Attachment" pptx

Báo cáo khoa học:

Báo cáo khoa học: "An Unsupervised Model for Statistically Determining Coordinate Phrase Attachment" pptx

... statistical model for determining the at- tachment of ambiguous coordinate phrases (CP) of the form nl p n2 cc n3. The model pre- sented here is based on JAR98], an unsupervised model for determining ... An Unsupervised Model for Statistically Determining Coordinate Phrase Attachment Miriam Goldberg Central High School & Dept. of Computer and Information Science 200 ... able for training. Such a model is useful only for languages in which annotated corpora are available. Because an unsupervised model does not rely on such corpora it may be modified for use...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "An Unsupervised Model for Joint Phrase Alignment and Extraction" ppt

... reliability of the phrase pair. Itwill be high for common phrase pairs that are gen-erated directly from the model, and also for phrasesthat, while not directly included in the model, arecomposed ... (θ|E, F). (1)If θ takes the form of a scored phrase table, wecan use traditional methods for phrase- based SMT tofind P (e|f , θ) and concentrate on creating a model for P (θ|E, F). We decompose ... discounts for short phrases are lower thanthose of long phrases. In particular, phrase pairs oflength up to six (for example, |e| = 3, |f| = 3) aregiven discounts of nearly zero while larger phrasesare...
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Báo cáo khoa học: "An Unsupervised System for Identifying English Inclusions in German Text" doc

... Wewere therefore interested in determining the perfor-mance of a trained classifier for our task. We ex-perimented with a conditional Markov model taggerthat performed well on language-independent ... POS-tagger136does not perform with perfect accuracy particularlyon data containing foreign inclusions. Providing thetagger with this information is therefore not neces-sarily useful for this task, especially ... June 2005.c2005 Association for Computational LinguisticsAn Unsupervised System for Identifying English Inclusions in German TextBeatrice AlexSchool of InformaticsUniversity of EdinburghEdinburgh,...
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Tài liệu Báo cáo khoa học: "A Statistical Model for Unsupervised and Semi-supervised Transliteration Mining" pptx

... cross-product list. For example, the underscore is defined as a word boundary for English WIL phrases. This assumption is not followed for cer-tain phrases like ”New York” and ”New Mexico”.473 Unsupervised ... labelled information for training. Our sys-tem extracts transliteration pairs in an unsupervised fashion. It is also able to utilize labelled informationif available, obtaining improved performance.We ... present a novel model of transliteration min-ing defined as a mixture of a transliteration model and a non-transliteration model. The transliteration model is a joint source channel model (Li et...
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Báo cáo khoa học: "An Ensemble Model that Combines Syntactic and Semantic Clustering for Discriminative Dependency Parsing" pptx

... individual models, the model with Brown semantic clusters clearly outper-forms the baseline, but the two models with syntac-tic clusters perform almost the same as the baseline.The ensemble model ... is our ensemble model which is the lin-ear combination of the three cluster-based models.As Table 1 shows, the ensemble model has out-performed the baseline and individual models in al-most ... accurate models into a more powerful model. In this paper, we construct the base modelsbased on different syntactic/semantic clusters usedin the features in each model. Our ensemble parsingmodel...
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Báo cáo khoa học: "A Bayesian Model for Unsupervised Semantic Parsing" ppt

... θc,t[draw sem class for arg]GenSemClass(cc,t) [recurse]Figure 2: The generative story for the Bayesian model for unsupervised semantic parsing.tributions over syntactic paths for the argumenttype ... of the Association for Computational Linguistics, pages 1445–1455,Portland, Oregon, June 19-24, 2011.c2011 Association for Computational LinguisticsA Bayesian Model for Unsupervised Semantic ... InferenceIn our model, latent states, modeled with hierarchi-cal PY processes, correspond to distinct semanticclasses and, therefore, their number is expected tobe very large for any reasonable model...
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Báo cáo khoa học: "An Unsupervised Morpheme-Based HMM for Hebrew Morphological Disambiguation" pdf

... this model, we found 834entries for the Π vector (which models the distri-bution of tags in first position in sentences) out ofpossibly N = 1934, about 250K entries for the Amatrix (which models ... guidelineswe published and checked for agreement. The testcorpus contains about 30K words. We comparedtwo unsupervised models over this data set: Word model [W], and Morpheme model [M]. We alsotested ... reduc-tions in the range: 11.5% – 37.8% (82.01 – 84.08 for word model 1, and 81.53 – 88.5 for morhpeme model 2-) were achieved by initializing the variousmodels with context-free approximations. Whilethis...
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Tài liệu Báo cáo khoa học: "Minimum Cut Model for Spoken Lecture Segmentation" ppt

... three lectures is-used for estimating the optimal word block length for representing nodes, the threshold distances for discarding node edges, the number of uniformchunks for estimating tf-idf ... did not try to ad-just our model to optimize its performance on thesynthetic data. The smoothing method developed for lecture segmentation may not be appropriate for short segments ranging from ... Graph-based Representation of TextFormalizing the Objective Whereas previous unsupervised approaches to segmentation restedon intuitive notions of similarity density, we for- malize the objective of...
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Tài liệu Báo cáo khoa học: "An Ensemble Method for Selection of High Quality Parses" pdf

... higher. Figure 1 demonstratesthese phenomena for two leading models, Collins(1999) model 2, a generative model, and Charniakand Johnson (2005), a reranking model. The parseradaptation scenario is ... Experimental SetupWe performed experiments with two parsing mod-els, the Collins (1999) generative model number2 and the Charniak and Johnson (2005) reranking model. For the first we used a reimplementation(?). ... clutter, for the filter f-score measure we use the maximumrecall (MR) baseline rather than the minimum length(ML) baseline, since the former outperforms the lat-ter. Thus, ML is only shown for the...
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Tài liệu Báo cáo khoa học: "An Approximate Approach for Training Polynomial Kernel SVMs in Linear Time" doc

... Association for Computational LinguisticsAn Approximate Approach for Training Polynomial Kernel SVMs in Linear Time Yu-Chieh Wu Jie-Chi Yang Yue-Shi Lee Dept. of Computer Science and Information ... function (4) for each support vector xi. The situation is even worse when the number of support vectors become huge (Kudo and Matsumoto, 2004). Therefore, whether in training or testing phrase, ... feature conjunctions. However, the training and testing time costs for polynomial kernel SVM is far slow than the linear kernel. For example, it took one day to train the CoNLL-2000 task with...
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