arabic part of speech tagging using the sentence structure
Tài liệu Báo cáo khoa học: "Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection" pptx
... Yoram Singer. 2003. Feature-Rich Part- of- Speech Tagging with a Cyclic Dependency Network.In Proceedings of the Annual Conference of the NorthAmerican Chapter of the Association for Computa-tional ... Proceedings of the 45th Annual Meet-ing of the Association of Computational Linguistics,ACL’07, pages 760–767.Anders Søgaard. 2011. Semi-supervised condensednearest neighbor for part- of- speech tagging. ... 363–367,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational LinguisticsFast and Robust Part- of- Speech Tagging Using Dynamic Model SelectionJinho D. ChoiDepartment of Computer...
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Tài liệu Báo cáo khoa học: "Arabic Tokenization, Part-of-Speech Tagging and Morphological Disambiguation in One Fell Swoop" pdf
... canexpress these features. We discuss the training anddecoding of these classifiers in Section 5.Third, we choose among the analyses returned by the morphological analyzer by using the output of the ... onlywhen the nominal subject precedes the verb. We use the tagset here only to compare to previous work.Instead, we advocate using a reduced part- of- speech tag set,9along with the other orthogonal ... chosenfor the input word in training.8 The ATB generates normalized forms of certain clitics and of the word stem, so that the resulting tokens are not simply the result of splitting the original...
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Tài liệu Báo cáo khoa học: "Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments" pdf
... performpoorly on Twitter (Finin et al., 2010).One of the most fundamental parts of the linguis-tic pipeline is part- of- speech (POS) tagging, a basicform of syntactic analysis which has countless appli-cations ... to test the efficacy of this feature set for part- of- speech tagging given lim-ited training data. We randomly divided the set of 1,827 annotated tweets into a training set of 1,000(14,542 tokens), ... this way, we tag hashtags with theirappropriate part of speech, i.e., as if they did not startwith #. Of the 418 hashtags in our data, 148 (35%)were given a tag other than #: 14% are proper nouns,9%...
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Tài liệu Báo cáo khoa học: "A Fully Bayesian Approach to Unsupervised Part-of-Speech Tagging∗" docx
... .5.ity of the transition distributions, are stronger than the effects of β, which determines the probability of the output distributions. The optimal value of .003 for α reflects the fact that the ... of the same randomized sets of sentences used by Smith and Eisner. Note that training on sets of contiguous sentences from the beginning of the treebank con-sistently improves our results, often ... of 74.5%,and is closer to the 90.1% accuracy of CRF/CE on the same data set using oracle parameter selection. The effects of α, which determines the probabil-2Results of CRF/CE depend on the...
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Báo cáo khoa học: "A Cost Sensitive Part-of-Speech Tagging: Differentiating Serious Errors from Minor Errors" pptx
... performed in the early step of NLP tasks, the errors in POS tagging are critical in that theyaffect subsequent steps and often lower the overallperformance of NLP tasks.Previous studies on POS tagging ... NN(d) The correct parse tree of the sentence “We altered. . .”.Figure 1: An example of POS tagging errors the correct one in Figure 1(d). That is, a sentence analyzed with this type of error ... Proceedings of the North American Chapter of the Association forComputational Linguistics. pp. 582–590.Thorsten Brants. 2000. TnT-A Statistical Part- of- Speech Tagger. In Proceedings of the Sixth...
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Báo cáo khoa học: "Efficient Optimization of an MDL-Inspired Objective Function for Unsupervised Part-of-Speech Tagging" docx
... between the explanation of the data by the model and the complexity of the model itself. Inspired by the MDLprinciple, we develop an objective func-tion for generative models that captures the ... A formalization of Ockham’s Razor,it says that the parameters are to be chosen thatminimize the description length of the data given the model plus the description length of the modelitself.It ... (3) The EM algorithm can be used to find a solution.However, we would like to maximize likelihoodand minimize the size of the model simultane-ously. We define the size of a model as the numberof...
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Báo cáo khoa học: "Semisupervised condensed nearest neighbor for part-of-speech tagging" pot
... WCNN C′from the new dataset which is a mixture of labeled and unlabeled datapoints. See Figure 4 for details.3 Part- of- speech tagging Our part- of- speech tagging data set is the standarddata ... let a model trained on the labeled data label the unlabeled data points and then to retrain the modelon the mixture of the original labeled data and the newly labeled data. The nearest neighbor ... thus of the form (one data point or wordper line):JJ JJ 17*NNS NNS 1IN IN 428DT DT 425where the first column is the class labels or the gold tags, the second column the predicted tags andthe...
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Báo cáo khoa học: "A Cascaded Linear Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging" pdf
... several other sub-models using additionalones such as word or POS n-grams, then trained the outside-layer linear model using the outputs of thesesub-models, including the perceptron. Since the per-ceptron ... (2004), the segmentationtask can be transformed to a tagging problem by as-signing each character a boundary tag of the follow-ing four types:• b: the begin of the word• m: the middle of the ... position of p, we cal-culate the scores of the word LM, the POS LM, the labelling probability and the generating probability,901To alleviate overfitting on the training examples,we use the refinement...
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Báo cáo khoa học: "Machine Aided Error-Correction Environment for Korean Morphological Analysis and Part-of-Speech Tagging" pptx
... plifying the format of error rule. As a result of experiment, about 63.2% of tagging errors were corrected. Our environment needs further enhance- ments. One is the need of observation on the ... Causes of Part- of- Speech Tagging Error We will mention important causes to make POS tagging errors. The first cause comes from the low accuracy at tagging unknown words, since assigning the most ... of total errors by resolving unknown words. With the increasing number of entries, the probability of unknown word occurrence will decrease. 6 Conclusion As the researches on the basis of...
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Báo cáo khoa học: "Categorial Fluidity in Chinese and its Implications for Part-of-speech Tagging" pptx
... via the design of the tagset. In thatcase the final lexicon would be theoretically validon the one hand, and the tagged corpus would be of practical use for NLP tasks (e.g. parsing) on the other. ... the organisa-tion of the lexicon.4.2 The TagsetHence even if the ambiguities are still in the tran-sitional stage and should not be kept in the lexi-con, it is still preferable to have them ... approach, each tag consists of aletter code for the general classification (i.e.noun, verb, etc.) of the word, and another for the sub-classification according to the particular con-text. For...
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Báo cáo khoa học: "Feature-Rich Part-of-speech Tagging for Morphologically Complex Languages: Application to Bulgarian" docx
... achieving accuracy of 97.98%, which is a significant improve-ment over the state -of- the- art for Bulgarian.1 Introduction Part- of- speech (POS) tagging is the task of as-signing each of the words in ... application of the 70 linguistic rules.Table 1 illustrates the effect of the rules on a small sentence fragment. In this example, the rules haveleft only one tag (the correct one) for three of the ambiguous ... concatenated to the beginning of the word-form in order to produce the lemma.Here is an example of such a rule:if tag = Vpitf-o1s then{remove ; concatenate } The application of the above rule to the...
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Báo cáo khoa học: "A Stacked Sub-Word Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging" potx
... the reference of previous systems thatrepresent state -of- the- art results. The comparison of the accuracy between our stacked sub-word systemand the state -of- the- art systems in the literature ... SegCandSegTagLare the predictions of the three coarse-grained solvers. For the three words at the begin-ning and the two words at the end, the three predic-tors agree with each other. And these five ... em-pirical upper bound of the sub-word tagging. The oracle performance of the final POS tagging on the development data set is shown in Table 4. The up-per bound indicates that the coarse search proceduredoes...
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Báo cáo khoa học: "Minimized Models for Unsupervised Part-of-Speech Tagging" pot
... MDL, thereis a single objective function to (1) maximize the likelihood of observing the data, and at the sametime (2) minimize the length of the model descrip-tion (which depends on the model ... measure the quality of the two observedgrammars/dictionaries by computing their preci-sion and recall against the grammar/dictionary weobserve in the gold tagging. 4We find that preci-sion of the ... accuracy when using a 17-tagset (a coarser-grained version of the tag labels from the PennTreebank) instead of the 45-tagset. When tag-ging the same standard test corpus with the smaller17-tagset,...
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Báo cáo khoa học: "Unsupervised Part-of-Speech Tagging Employing Efficient Graph Clustering" ppt
... number of approaches to derive syntactic categories. All of them employ a syntactic version of Harris’ distributional hypothesis: Words of similar parts of speech can be observed in the same ... co-occurrences as ranked by the log-likelihood reflect the typical immediate contexts of the word. Regarding the highest ranked neighbours as the profile of the word, it is possible to assign ... Proceedings of the HLT-NAACL-06 Workshop on Textgraphs-06, New York, USA E. Charniak, C. Hendrickson, N. Jacobson and M. Perkowitz. 1993. Equations for part- of- speech tagging. In Proceedings of the...
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Báo cáo khoa học: "Revision Learning and its Application to Part-of-Speech Tagging" pptx
... the set of classes,# xi: the ith training example,# yi∈ C: the class of xi,# k: the number of classes,# l: the number of training examples,# ni: the ordered indexes of C# (see the ... µ, we use the following featuresfor the SVMs:1. the POS tags, the lexical forms and the in-flection forms of the two morphemes pre-ceding µ;2. the POS tags and the lexical forms of the two ... repeat the following revision learning process backwarduntil the beginning of the sentence. Rankingsare calculated by HMMs to all the nodes con-nected to the current state node, and the best of these...
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