a part of speech estimation method
Tài liệu Báo cáo khoa học: "A Fully Bayesian Approach to Unsupervised Part-of-Speech Tagging∗" docx
... probabilityover a range of possible parameters, and per-mits the use of priors favoring the sparsedistributions that are typical of natural lan-guage. Our model has the structure of a standard ... no gold standard available. Luckily, the Bayesianapproach allows us to automatically select valuesfor the hyperparameters by treating them as addi-tional variables in the model. We augment the ... optimal set of parameter values, we seek to directly maximize theprobability of the hidden variables given the ob-served data, integrating over all possible parame-ter values. Using part- of- speech...
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Báo cáo khoa học: "A Cost Sensitive Part-of-Speech Tagging: Differentiating Serious Errors from Minor Errors" pptx
... 43–46.Sharon Goldwater and Thomas T. Griffiths. 2007. A fully Bayesian Approach to Unsupervised Part- of- Speech Tagging. In Proceedings of the 45th AnnualMeeting of the Association of Computational ... 265–292.Dipanjan Das and Slav Petrov. 2011. Unsupervised Part- of- Speech Tagging with Bilingual Graph-Based Pro-jections. In Proceedings of the 49th Annual Meeting of the Association of Computational ... Com-putational Natural Language Learning. pp. 296–305.Taku Kudo, Kaoru Yamamoto, and Yuji Matsumoto.2004. Applying Conditional Random Fields toJapanese Morphological Analysis. In Proceedings of the...
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Báo cáo khoa học: "A Cascaded Linear Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging" pdf
... at the same time, we expand boundarytags to include POS information by attaching a POSto the tail of a boundary tag as a postfix followingNg and Low (2004). As each tag is now composed of a ... segmentationand POS tagging (Joint S&T). Since the typical ap-proach of discriminative models treats segmentationas a labelling problem by assigning each character a boundary tag (Xue and ... i a N-best list of candidate results from all these candidates. Whenwe derive a candidate result from a word-POS pairp and a candidate q at prior position of p, we cal-culate the scores of...
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Báo cáo khoa học: "A Comparative Study of Parameter Estimation Methods for Statistical Natural Language Processing" potx
... Linguistics A Comparative Study of Parameter Estimation Methods for Statistical Natural Language Processing Jianfeng Gao*, Galen Andrew*, Mark Johnson*&, Kristina Toutanova* *Microsoft ... Introduction Parameter estimation is fundamental to many sta-tistical approaches to NLP. Because of the high-dimensional nature of natural language, it is often easy to generate an extremely large ... Lasso (L1) regularization. We first investigate all of our estimators on two re-ranking tasks: a parse selection task and a language model (LM) adaptation task. Then we apply the best of...
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Báo cáo khoa học: "A Practical Solution to the Problem of Automatic Part-of-Speech Induction from Text" pdf
... (1992). Class-based n-gram models of natural language. Computa-tional Linguistics 18(4), 467-479. Clark, Alexander (2003). Combining distributional and morphological information for part of speech ... data sparseness can be minimized by reducing the dimensionality of the matrix. An appropriate alge-braic method that has the capability to reduce the dimensionality of a rectangular matrix ... are much more salient. Also, widely and rural are well within the adjective cluster. The comparison of the two dendrograms indicates that the SVD was capable of making ap-propriate generalizations....
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Báo cáo khoa học: "A Hierarchical Pitman-Yor Process HMM for Unsupervised Part of Speech Induction" doc
... that resultin the same tagging, at all levels in the hierarchy:tag trigrams, bigrams and unigrams; and also words,character bigrams and character unigrams. To avoidthis rather onerous marginalisation2we ... Natu-ral Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP), pages504–512.Noah A. Smith and Jason Eisner. 2005. Contrastive estimation: Training log-linear ... bigramdistribution. A hierarchy of PYPs can be formed by making thebase distribution of a PYP another PYP, following a 868state -of- the-art results across a range of corpora andlanguages.2 BackgroundPast...
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A Study of Channel Estimation for OFDM Systems and System Capacity for MIMO-OFDM Systems
... increasing demands of high data transmission rate and reliable communication quality, channel estimation has become a necessary part in the OFDM system. For example, the digital video broadcasting ... 4.3.4. Summary of the proposed channel estimation and data detection 98 4.4. Analysis of MSE of the proposed channel estimation method 99 4.4.1. MSE analysis of channel estimation for the ... transmitting data spread over a large bandwidth (usually larger than 500 MHz) that shares among users. UWB was traditionally applied in non-cooperative radar imaging. Most recent applications include...
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part of speech
... The speaker announced the of a new college. ESTABLISH147. We want to students to participate fully in the running of the college. COURAGE148. Details of the are available at all participating ... mixture of the two.FRUSTRATE139. Researchers in this field have made some important new DISCOVER140. is part of the American character. GENEROUS141. , his wife was killed in a car accident. TRAGIC142. ... musically and it is very effective. LYRICS133. She promised not to say a word to anyone about it. SOLEMN134. What unusual of flavours! COMBINE135. His was a combination of surgery, radiation and...
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Tài liệu Báo cáo khoa học: "Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection" pptx
... Ogren, WayneWard, James H. Martin, Guergana Savova, and MarthaPalmer. 2010. An architecture for complex clinicalquestion answering. In Proceedings of the 1st ACMInternational Health Informatics ... of the Associa-tion for Computational Linguistics: Human LanguageTechnologies, ACL’11, pages 48–52.Drahom´ıra ”johanka” Spoustov´ a, Jan Hajiˇc, Jan Raab,and Miroslav Spousta. 2009. Semi-supervised ... in atleast 3 documents of the training data are used. For a domain-specific model, we use a threshold of 1.The generalized and domain-specific models aretrained separately; their learning parameters...
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- part of speech disambiguation
- part of speech induction
- part of speech tagging
- a comparative study of parameter estimation methods
- load of part of speech blocks
- part of speech tagger
- a framework of feature selection methods
- unsupervised part of speech induction
- a comparative study of parameter estimation methods for statistical natural language processing
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