extracting emotional polarity of words using spin model
Tài liệu Báo cáo khoa học: "Extracting Semantic Orientations of Words using Spin Model" pdf
... :¯xnewi=xixiexpβxijwij¯xoldjxiexpβxijwij¯xoldj. (7)4 Extraction of Semantic Orientation of Words with Spin Model We use the spin model to extract semantic orienta-tions of words. Each spin has a direction taking one of two values:up or ... en-ergetically tend to have the same spin. This model is called the Ising spin model, or simply the spin model (Chandler, 1987). The energy function of a spin system can be represented asE(x, W ) ... calculate values of m with several different values of β and select thevalue just before the phase transition.4.4 Discussion on the Model In our model, the semantic orientations of words are determined...
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Báo cáo khoa học: "Unsupervised Segmentation of Words Using Prior Distributions of Morph Length and Frequency" ppt
... segmenta-tion of a set of words consists of the following steps:(1) Segment the words in the corpus using the au-tomatic segmentation algorithm.(2) Divide the segmented data into two parts of equal ... does not makeuse of explicit prior information.Furthermore, the possible benefit of using thetwo sources of prior information can be comparedagainst the possible benefit of grouping stems andsuffixes ... of thetext produced by the Connexor FDG parser.13The English corpus consists of mainly newspapertext (with non -words removed) from the Brown cor-pus.14A morphological analysis of the words...
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Báo cáo khoa học: "A Part of Speech Estimation Method for Japanese Unknown Words using a Statistical Model of Morphology and Context" pptx
... ~-~,~! resented all unknown words by one length model. Figure 2 shows the word length distribution of words consists of only kanji characters and words consists of only katakana characters. ... We present a statistical model of Japanese unknown words using word morphology and word context. We find that Japanese words are better modeled by clas- sifying words based on the character ... accuracy of four unknown word models over test set-2. Com- pared to the baseline model (Poisson + bigram), by using word type and part of speech information, the precision of the proposed model...
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Báo cáo khoa học: "Improved Modeling of Out-Of-Vocabulary Words Using Morphological Classes" docx
... morphologicallanguage model. In an experiment the model outper-formed a modified Kneser-Ney model, especially inthe prediction of the continuations of histories con-taining OOV words. The model is entirely ... threshold of one andin the distribution of OOV words (cf. Table 2). Thec1 model with θ = 1 is specialized for predicting words after unknown nouns and cardinal numbersand two thirds of the unknown ... SetupWe compare the performance of the described model with a Kneser-Ney model and an interpolated model based on part -of- speech (POS) tags. The relation be-tween words and POS tags is many-to-many,...
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Tài liệu Báo cáo khoa học: "Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection" pptx
... Robust Part -of- Speech Tagging Using Dynamic Model SelectionJinho D. ChoiDepartment of Computer ScienceUniversity of Colorado Boulderchoijd@colorado.eduMartha PalmerDepartment of LinguisticsUniversity ... taggingaccuracies of all tokens and unknown tokens, re-spectively. Our individual models (Models D andG) give comparable results to the other systems. Model G performs better than Model D for BC, ... generalized model shows itsstrength in tagging data that differs from the train-ing data. The dynamic model selection approach (Model S) shows the most robust results across gen-res, although Models...
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Tài liệu Báo cáo khoa học: "Enhanced word decomposition by calibrating the decision threshold of probabilistic models and using a model ensemble" pdf
... analysis of text (CHEAT). Proceed-ings of the PASCAL Challenges Workshop on Un-supervised Segmentation of Words into Morphemes,Venice, Italy.M. Creutz. 2006. Induction of the Morphology of Nat-ural ... order model whereasPROMODES-H is a novel development of PRO-MODES with a higher order model. For bothalgorithms, we defined the mathematical model and performed experiments on language data of the ... net increase of 0.0819 of correct boundaries which led to the in-creased recall. Since the deduction of precisionis less than the increase of recall, a better over-allperformance of PROMODES-H...
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Tài liệu Báo cáo khoa học: "Modeling Wisdom of Crowds Using Latent Mixture of Discriminative Experts" docx
... direction of research appeared in thelast decade, taking full advantage of the ”wisdom of crowds” (Surowiecki, 2004). In simple words, wis-dom of crowds enables parallel acquisition of opin-ions ... samenumber of head nods as the actual listener. See Fig-ure 1 for a graphical representation of CRF model. CRF Mixture of Experts To show the importance of latent variable in our Wisdom-LMDE model, ... graphicalrepresentation of a CRF Mixture of experts is givenin the Figure 1.Actual Listener (AL) Classifiers This baseline model consists of two models: CRF and LDCRF chains(See Figure 1). To train these models,...
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Tài liệu Báo cáo khoa học: "An Evaluation Method of Words Tendency using Decision " docx
... Number of correct words extracted by (DT) Precision = Total number of words extracted by (DT) Number of correct words extracted by DT) Recall = ❈❈❈❈❈❈ Total number of correct words ... classes of the input analysis data (test data). 2. POPULARITY OF WORDS CONSIDERING TIME-SERIES VARIATION 2.1 Stability Classes of the Words: To judge the index of popularity of words with ... divided by the total frequencies of the words in each group. Table 1 Sample of Classified Words Stability Class Example of words in each class Increasing Words Sammy-Sosa, McGwire, Carlos-Delgado...
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Báo cáo khoa học: "Extracting Opinion Expressions and Their Polarities – Exploration of Pipelines and Joint Models" pot
... Figure 1.Base polarity classifier score. Sum of the scoresfrom the polarity classifier for every opinion. Polarity pair. For every pair of opinions in thesentence, we add the pair of polarities: ... is extracted sinceneither of the expressions dominates the other. Polarity pair and word pair. The polarity pairconcatenated with the words of the clos-est nodes of the two expressions: NEGA-TIVE+NEGATIVE+appeasement+terrorists. Polarity ... demon-strate the benefit of integrating opinion ex-traction and polarity classification into a joint model using features reflecting the global po-larity structure. The model is trained using large-margin...
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Báo cáo khoa học: Natriuretic peptide system: an overview of studies using genetically engineered animal models doc
... professor of the University of Texas, whose com-ments and suggestions were of inestimable value for ourstudy using GC-A knockout mice, to Professor Misono of the University of Nevada School of ... cardioprotectiveactions of PKG in pathological conditions such as‘Circulating hormones’ANPBNPVasodilatationNatriuresisGC-AANPBNP‘Local hormones’Inhibition of Cardiac remodelingGC-AReduction of cardiac ... peptide system: an overview of studies using genetically engineered animal modelsIchiro Kishimoto1,2, Takeshi Tokudome1, Kazuwa Nakao3and Kenji Kangawa11 Department of Biochemistry, National...
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Báo cáo khoa học: "Guessing Parts-of-Speech of Unknown Words Using Global Information" ppt
... distribution of thepart -of- speech of the kth occurrence of the un-known words given a set of local contexts w, andis calculated as an expected value over the distri-bution of the unknown words as ... unknown words appear are also identified.Thus, we focus only on prediction of the POS tags of unknown words. In the rest of this section, we first present a model for POS guessing of unknown words ... distribution of the parts -of- speech of all occurrences of theunknown words in a document which have thesame lexical form. We suppose that such parts- of- speech have correlation, and the part -of- speechof...
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Báo cáo " Eutrophycation assessment and prediction of Bay Mau Lake using mathematical models " doc
... eutrophycation is the use of mathematical models. In this paper, we used the Vollenweider model, empirical watershed model and Jorgensen model to determine the eutrophycation of Bay Mau Lake by phosphorous ... model to determine standard amount of phosphorus loading to the lake annually. - Use the empirical watershed model and the eutrophycation model of Jorgensen to calculate the supplement of ... phosphorus load We used empirical watershed model and Jorgensen model to calculate the total amount of phosphorus load. By Jorgensen model, the amount of P load is 93 - 211.9 times higher than...
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Báo cáo khoa học: "Predicting Part-of-Speech Information about Unknown Words using Statistical Methods" pptx
... smoothing using the open-class tag distri- bution, instead of the overall distribution, will offer better results. 3.3 Contextual Information Contextual probabilities offer another source of information ... Part -of- Speech Information about Unknown Words using Statistical Methods Scott M. Thede Purdue University West Lafayette, IN 47907 Abstract This paper examines the feasibility of using ... part -of- speech tagger to handle out -of- lexicon words. 1 Introduction Part -of- speech tagging involves selecting the most likely sequence of syntactic categories for the words in a sentence. These syntactic...
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modeling and simulation of systems using matlab and simulink
... are examples of physical models (also called iconic models), and are not typical of the kinds of models that are of interest in operations research and system analysis. Physical models are most ... Control 4379.4.4 Modeling of Various Components of Pitch Control System 4389.4.5 Simulink Model of Pitch Control in Flight 4409.4.5.1 Simulink Model of Pitch Control in Flight Using Nonlinearities ... vast majority of models built for such purposes are abstracted, FIGURE 2.1Different modeling approaches.AccuracyMathematical models ANN modelsFuzzy modelsComplexity Systems Modeling 67I=0.5;b=0.5;k=0.1;A...
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