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phụ lục 02 phân tích chi tiết một số ca sử dụng khác

Dự đoán và phân tích các trạng thái của Histone trong chuỗi DNA bằng phương pháp conditional random fields

Dự đoán và phân tích các trạng thái của Histone trong chuỗi DNA bằng phương pháp conditional random fields

Công nghệ thông tin

... phương pháp có tên ChIP-chip (còn gọi ChIP-on-chip) [21] ChIP-chip phương pháp sử dụng nhiều công nghệ sinh học nói chung việc khám phá mối quan hệ DNA protein nói riêng ChIP-chip sử dụng công nghệ ... H2A, H2B) Có nhiều nghiên cứu khác sử dụng phương pháp này, nhiên khác thể độ phân giải (resolution) phương pháp Độ phân giải ChIP-chip phụ thuộc vào hai yếu tố: chi u dài đoạn chromatin làm giàu ... oligonucleotide mật độ cao (chip) Sau quét (scan) hình ảnh thiết bị sinh học thu hình ảnh đoạn DNA thể màu Lựợc đồ phương pháp ChIP-chip mô tả Hình 15 Khi sử dụng phương pháp ChIP-chip với toán xác...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "Conditional Random Fields for Word Hyphenation" docx

Báo cáo khoa học

... words Perhaps more important for largescale publishing applications, our system is about six times faster at syllabifying new text The speed comparison is fair because the computer we use is slightly ... show that CRFs can achieve extremely good performance on the hyphenation task History of automated hyphenation The earliest software for automatic hyphenation was implemented for RCA 301 computers, ... therefore of considerable practical and commercial importance Over the years, various machine learning methods have been applied to the hyphenation task However, none have achieved high accuracy One...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields" pdf

Báo cáo khoa học

... method presented here and CRR07 cannot be exact The technique described in CRR07 can be applied in two ways: constraints can be applied during learning, and they can also be applied during inference ... labeling In COLING/ACL Thorsten Joachims 1999 Transductive inference for text classification using support vector machines In ICML S Kakade, Y-W Teg, and S.Roweis 2 002 An alternate objective function ... Jaakkola 2 002 Partially labeled classification with markov random walks In NIPS, volume 14 X Zhu and Z Ghahramani 2 002 Learning from labeled and unlabeled data with label propagation Technical Report...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "Discriminative Word Alignment with Conditional Random Fields" ppt

Báo cáo khoa học

... mathematics of statistical machine translation: Parameter estimation Computational Linguistics, 19(2):263–311 C Callison-Burch, D Talbot, and M Osborne 2004 Statistical machine translation with ... used by six Canadian experts related to the provision of technical assistance ii ( ii ) ( a ) Three vehicles will be used by six Canadian experts related to the provision of technical assistance ... la de prestation le cadre dans canadiens par spécialistes seront utilisés véhicules ) ) a ( (a) With Markov features ii technique de aide la prestation le de cadre dans canadiens spécialistes...
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Tài liệu Báo cáo khoa học:

Tài liệu Báo cáo khoa học: "Improving the Scalability of Semi-Markov Conditional Random Fields for Named Entity Recognition" pdf

Báo cáo khoa học

... information is important Micahel Krauthammer and Goran Nenadic 2004 Term identification in the biomedical literature Jornal of Biomedical Informatics John Lafferty, Andrew McCallum, and Fernando Pereira ... Yusuke Miyao and Jun’ichi Tsujii 2 002 Maximum entropy estimation for feature forests In Proc of HLT 2 002 Peshkin and Pfeffer 2003 Bayesian information extraction network In IJCAI Sunita Sarawagi ... labels does not necessarily provide useful information because, in many cases, the previous label of a named entity is “O”, which indicates a non-named entity For 98.0% of the named entities...
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Báo cáo khoa học:

Báo cáo khoa học: "Efficient, Feature-based, Conditional Random Field Parsing" potx

Báo cáo khoa học

... In our case the values in the chart are the clique potentials which are non-negative numbers, but not probabilities this case the gains from adding additional clients decrease rapidly, because ... that this property is satisfied, without scaling, for objective functions that sum over the training data, as it is in our case, but any priors must be scaled down by a factor of b/ |D| The stochastic ... WSJ40 runs we used a simple, right branching binarization where each active state is annotated with its previous sibling and first child This is equivalent to children of a state being produced by...
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Báo cáo khoa học:

Báo cáo khoa học: "Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech" pptx

Báo cáo khoa học

... number of canonical phones binned into equal categories • Log Speech Rate; calculated on strings of speech bounded on either side by pauses of 300 ms or greater and binned into equal categories ... Phonological variables The last category of predictors, phonological variables, concern aspects of rhythm and timing of an utterance We have two main sources for these variables: those that can be ... the utterance length Below is the list of our textual features: • Number of canonical syllables • Number of canonical phones • Number of transcribed phones • The length of the utterance in number...
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Báo cáo khoa học:

Báo cáo khoa học: "Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling" pdf

Báo cáo khoa học

... one can measure the precision, recall and F-measure, given by # correct predictions precision = # predicted gene mentions # correct predictions recall = # true gene mentions precision recall ... S Wright (2000) Numerical Optimization, Springer U K Nigam, A McCallum, S Thrun and T Mitchell (2000) Text classification from labeled and unlabeled documents using EM Machine learning 39(2/3):135-167 ... (2005) Conditional random field biomedical entity tagger [http://www.seas.upenn.edu/ sryantm/software/BioTagger/] ƒ Therefore A McCallum (2 002) MALLET: A machine learning for language toolkit [http://mallet.cs.umass.edu]...
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Báo cáo khoa học:

Báo cáo khoa học: "Training Conditional Random Fields with Multivariate Evaluation Measures" potx

Báo cáo khoa học

... regularization term can be rewritten in the following form: (5) y ∈Y\y where y ∗ is the correct output for x Here it can be noted that, for a given x, d() ≥ indicates misclassification By using d(), ... (CoNLL) 2000, 2 002 and 2003, are typical CRF applications These tasks require the extraction of pre-defined segments, referred to as target segments, from given texts Fig shows typical examples of ... incorrect output As we know, the maximum output can be efficiently calculated with the Viterbi algorithm, which is the same as calculating Eq Therefore, we can find the maximum incorrect output by using...
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Báo cáo khoa học:

Báo cáo khoa học: "Fast Full Parsing by Linear-Chain Conditional Random Fields" docx

Báo cáo khoa học

... significantly better than previous cascaded chunking approaches such as Tsuruoka & Tsujii (2005) and Tjong Kim Sang (2001) Although the comparison presented in the table is not perfectly fair because ... recently, Brants (1999) used a cascaded Markov model to parse German text Tjong Kim Sang (2001) used the IOB tagging method to represent chunks and memory-based learning, and achieved an f-score of 80.49 ... w0 (up to length 10) w0 has a hyphen w0 has a number w0 has a capital letter w0 is all capital N(w0 ) the current word by lowering capital letters and converting all the numerals into ‘#’, and...
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Báo cáo khoa học:

Báo cáo khoa học: "Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums" docx

Báo cáo khoa học

... able to capture the dependency The context detection can be modeled as a classification problem Traditional classification tools, e.g SVM, can be employed, where each pair of question and candidate ... Proceedings of IJCAI J Jeon, W Croft, and J Lee 2005 Finding similar questions in large question and answer archives In Proceedings of CIKM T Joachims 1999 Making large-scale support vector machine learning ... (e.g the similarity between context and answer can be used as features in CRFs) The two-phase procedure, however, still cannot capture the non-local dependency between contexts and answers in...
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Báo cáo khoa học:

Báo cáo khoa học: "Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm" pptx

Báo cáo khoa học

... parallelizable, so that the computation can be divided among many processors Empirical Results We present empirical results on the Rich Transcription 2 002 evaluation test set (rt02), which we used as our development ... software libraries (Balay et al., 2 002; Benson et al., 2 002) This technique has been shown to be very effective in a variety of NLP tasks (Malouf, 2 002; Wallach, 2 002) The main interface between the ... all trigrams seen in Li The term log Qi (z|xy) can be calculated once before training for every lattice in the training set; the ExpCount term is calculated as before using the GRM library We...
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Báo cáo khoa học:

Báo cáo khoa học: "Scaling Conditional Random Fields Using Error-Correcting Codes" docx

Báo cáo khoa học

... Error-correcting output coding for text classification In Proceedings of IJCAI: Workshop on machine learning for information filtering 17 Hanna Wallach 2 002 Efficient training of conditional random ... Error-correcting CRF training Error-correcting codes can also be applied to sequence labellers, such as CRFs, which are capable of multiclass labelling ECOCs can be used with CRFs in a similar manner to ... sets, columns must be selected with care to maximise the inter-row and inter-column separation This can be done by randomly sampling the column space, in which case the probability of poor separation...
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Báo cáo khoa học:

Báo cáo khoa học: "Logarithmic Opinion Pools for Conditional Random Fields" ppt

Báo cáo khoa học

... collapse to category N • All types of verb collapse to category V • All types of adjective collapse to category J • All types of adverb collapse to category R • All other POS tags collapse to category ... derivative is tractable because we can use dynamic programming to efficiently calculate the pairwise marginal distribution for the LOP-CRF Using these expressions we can efficiently train the LOP-CRF ... labelling errors to examine the statistical significance of these results We test significance at the 5% level At this threshold, all the LOP-CRFs significantly outperform the corresponding unregularised...
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Báo cáo khoa học:

Báo cáo khoa học: "Using Conditional Random Fields For Sentence Boundary Detection In Speech" potx

Báo cáo khoa học

... here, but it is not implemented in the software we used (McCallum, 2 002) 453 E2 EN Ei O E i-1 Ei E i+1 O i-1 Oi O i+1 Figure 2: Graphical representations of a general CRF and the first-order CRF ... whereas, the Maxent model makes a local decision, as shown in Equation (2), without utilizing any state dependency information We use the Mallet package (McCallum, 2 002) to implement the CRF model ... entropy models Technical report, Carnegie Mellon University 458 H Christensen, Y Gotoh, and S Renal 2001 Punctuation annotation using statistical prosody models In ISCA Workshop on Prosody in Speech...
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accelerated training of conditional random fields with stochastic

accelerated training of conditional random fields with stochastic

Tin học

... IST-2 002- 506778, and an NSERC Discovery Grant References Barndorff-Nielsen, O E (1978) Information and Exponential Families in Statistical Theory Wiley, Chichester Besag, J (1986) On the statistical ... represent salient features of the data, and are typically chosen in an application-dependent manner as part of the CRF design for a given machine learning task Maximum a posteriori (MAP) estimation ... gt , (19) (21) where Ht vt is calculated efficiently via (11) Since θ0 does not depend on any gains, v0 = SMD thus introduces two scalar tuning parameters, with typical values (for stationary problems)...
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an introduction to conditional random fields for relational learning

an introduction to conditional random fields for relational learning

Tin học

... vocabulary Thus, in text applications, CRF features are typically binary; in other application areas, such as vision and speech, they are more commonly real-valued Third, in language applications, ... (left), and as a factor graph (right) Figure 1.1 1.2.2 Applications of graphical models In this section we discuss a few applications of graphical models to natural language processing Although these ... problematic because it can hurt performance For example, although the naive Bayes classifier performs surprisingly well in document classification, it performs worse on average across a range of applications...
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efficient training of conditional random fields.ps

efficient training of conditional random fields.ps

Tin học

... transition distributions and, in the case of states with a single outgoing transition, causes the observation to be effectively ignored The label bias problem can significantly undermine the benefits of ... performed did indicate that numerical optimisation techniques for CRF parameter estimation result in faster convergence than iterative scaling This is a highly promising result, indicating that such ... parameter λk can also be considered to be a weighting of indicating the informativeness of feature fk 3.4 Potential Functions for CRFs The maximum entropy framework provides significant justification...
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hidden conditional random fields for gesture recognition

hidden conditional random fields for gesture recognition

Tin học

... underlying graphical model captured spatial dependencies between hidden object parts In this work, we modify the original HCRF approach to model sequences where the underlying graphical model captures ... Expand Vertically (EV) arm gesture, the arms move vertically apart and return to the resting position In the Shrink Vertically (SV) gesture, both arms begin from the hips, move vertically together ... (i.e., that the state at time t can depend on observations that happened earlier or later in the sequence.) An HCRF can learn a discriminative state distribution and can be easily extended to incorporate...
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dynamic conditional random fields- factorized probabilistic models

dynamic conditional random fields- factorized probabilistic models

Tin học

... CRF+CRF and the FCRF is statistically significant by a two-sample t-test (p < 0. 002) In fact, there was no subset of the To simulate the effects of a cascaded architecture, the POS labels in the ... hierarchical hidden Markov model: Analysis and applications Machine Learning, 32, 41–62 Frietag, D., & McCallum, A (1999) Information extraction with HMMs and shrinkage AAAI Workshop on Machine ... that does the individual labeling tasks sequentially, and has potentially many practical implications, because cascaded models are ubiquitous in NLP Also, we have shown that using approximate inference...
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