Báo cáo khoa học: "A Sequencing Model for Situation Entity Classiﬁcation" pdf

... 896–903,Prague, Czech Republic, June 2007.c2007 Association for Computational LinguisticsA Sequencing Model for Situation Entity ClassificationAlexis Palmer, Elias Ponvert, Jason Baldridge, ... aspectual classification.5 ModelsWe consider two types of models for the automaticclassification of situation entities. The first, a la-beling model, utilizes a maximum entropy model to predict SE ... non-absolute, makingthem inappropriate for a rule-based model. Ourmodels handle the defeasibility of these correlationsprobabilistically, as is standard for machine learning for natural language processing.8994.3...

Tài liệu Báo cáo khoa học: "A Statistical Model for Unsupervised and Semi-supervised Transliteration Mining" pptx

... 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 ... labelled information for training. Our sys-tem extracts transliteration pairs in an unsupervisedfashion. It is also able to utilize labelled informationif available, obtaining improved performance.We ... of the Association for Computational Linguistics, pages 469–477,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational LinguisticsA Statistical Model for Unsupervised...

Báo cáo khoa học: A mouse model for in vivo tracking of the major dust mite allergen Der p 2 after inhalation docx

... University) for excellent technicalassistance. This work was supported by grants fromthe Swedish Foundation for Health Care Sciences andAllergy Research, the Swedish Research Council for Medicine ... the fate of an aller-gen upon inhalation, we addressed this issue for a major dust mite allergen,Der p 2. First, a model for Der p 2-sensitization was established inC57BL ⁄ 6 J mice, in which ... after inhalation are of crucial import-ance.Mice are used widely for in vivo models of allergyand asthma [16]. Common protocols for sensitizingmice involve immunization with allergen together...

Báo cáo khoa học: "A Probabilistic Model for Fine-Grained Expert Search" pptx

... different qualities. For example, both topic “css test” and “test suite” are the bi-gram matching for query “css test suite”; however, the former might be more informative. To model that, we use ... following sub-sections, we will detail two sub-models: the expert matching model P(c|e) and the evidence matching model P(e|q). 3.2 Expert Matching Model We expand the evidence e as quadruple ... An evidence-oriented probabilistic model for ex-pert search and a method for the implementa-tion are proposed. Experimental results show that the proposed model and the implementa-tion are...

Báo cáo khoa học: "A Bayesian Model for Discovering Typological Implications" ppt

... use a nearlyidentical model to the FLAT model, but instead ofhaving a single m variable, we have three: one for IE, one for Austronesian and one for “all languages.” For a general tree, we ... in Figure 3 (on a log-scale for the x-axis).The two best-performing models are the two hier-archical models. The flat model does significantlyworse and the random model does terribly. The ver-tical ... of perform-ing a simple Gibbs sample for m in Step (4), wefirst sample the m values for the internal nodes us-ing simple Gibbs updates. For the leaf nodes, weuse rejection sampling. For this...

Báo cáo khoa học: "A Morphographemic Model for Error Correction Nonconcatenative Strings" pot

... used, and subsection 2.2 describes the model. 2.1 The Formalism In order to handle the non-linear phenomenon of Arabic, our model adopts the two-level formalism presented by (Pulman and Hepple, ... first to appear on the left of LEx. In our morphographemic model, we add a similar formalism for expressing error rules (3). (3) ERROR FORMALISM ErrSurf =~ Surf { PLC- PRC } where PLC = partition ... represented in the orthographic form by special diacritics. 4For other issues with respect to syntactic dependencies, see (Abduh, 1990). Subsection 2.1 presents the formalism used, and subsection...

Báo cáo khoa học: "A Statistical Model for Lost Language Decipherment" pptx

... of the Association for Computational Linguistics, pages 1048–1057,Uppsala, Sweden, 11-16 July 2010.c2010 Association for Computational LinguisticsA Statistical Model for Lost Language DeciphermentBenjamin ... translations, mea-sured with respect to complete word-forms andmorphemes, for the HMM-based substitution ci-pher baseline, our complete model, and our model without the structural sparsity priors. ... generativeBayesian model. This model assumes that eachword in the lost language is composed of mor-phemes which were generated with latent coun-terparts in the known language. We model bilin-gual...

Báo cáo khoa học: "A Discriminative Model for Joint Morphological Disambiguation and Dependency Parsing" ppt

... of the Association for Computational Linguistics, pages 885–894,Portland, Oregon, June 19-24, 2011.c2011 Association for Computational LinguisticsA Discriminative Model for Joint Morphological ... Experimental ResultsWe compare the performance of the pipeline model (§4) and the joint model (§3) on morphological dis-ambiguation and unlabeled dependency parsing. Model Tagger Joint Tagger JointAttr. ... interpretations. Bothalso often have identical forms for different genders,numbers and cases. In these situations, syntacticconsiderations help nudge the joint model to the cor-rect interpretations.Experiments...

Báo cáo khoa học: "A global model for joint lemmatization and part-of-speech prediction" doc

... performance on both by sharing infor-mation between them. We present a joint model for these two subtasks: it is joint not only in thatit performs both tasks simultaneously, sharing in-formation, ... set sizes for differ-ent languages.We use three different lexicons for each lan-guage: one for training (LTrain), one for devel-opment (LDev), and one for testing (LTest). Theglobal model weights ... state-of-the art models for the two subtasks and performing joint inferencewe can improve performance on both tasks. Themain contribution of our work was that we intro-duced a joint model for the two...

Báo cáo khoa học: "A Probabilistic Model for Canonicalizing Named Entity Mentions" docx

... ofidentifying the correct team for every player. TheEEA model is not designed for this and performedpoorly. Our model can do better, since it makes useof context information and features, and ... result, the model discov-ers parts of names—Mrs., Michelle, Obama—while simultaneously performing coreference res-olution for named entity mentions. In the sportsnews dataset, the model is ... {is, in, of, for} }; 1{w is a person entity} ;1{w is an organization entity} .Forward and backward probabilities. Sincewe introduce ﬁrst-order dependencies betweencolumns, we have forward and...

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