word to sentence level emotion tagging
Tài liệu Báo cáo khoa học: "Word to Sentence Level Emotion Tagging for Bengali Blogs" doc
... respectively. 5 Sentence Level Emotion Tagging This module has been developed to identify sen-tence level emotion tags based on the word level emotion tags. 5.1 Calculation of Emotion Tag weights ... First sentence in a topic: It has been ob-served that first sentence of the topic gen-erally contains emotion (Roth et.al., 2005). SentiWordNet emotion word: A word appearing in the SentiWordNet ... Ekman’s six basic emotion tags. The assignment of emotion tag to a word has been done based on the type of the Emotion Word lists in which that word is pre-sent. Other non-emotional words have been...
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Báo cáo khoa học: "AN APPROACH TO SENTENCE-LEVEL TRANSLATION ANAPHORA IN MACHINE" ppt
... the comp -to- comp movement. Although other approaches, such as direct movement, are feasible too, we win adhere to the comp -to- comp approach. Data from Spanish (Torrego 1984) also seem to support ... the order of the slots is not in any way related to word order in the sentence. l°All I-structures are also their own ancestor according to the deft- nlt|onin (19a). This is the correct ... will have to be used in these cases. For an example of a lexical hole, compare sentence (1) and its translation into English (2). (1) Jan zwemt graag (2) John likes to swim Unlike sentences...
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Báo cáo khoa học: "Paragraph-, word-, and coherence-based approaches to sentence ranking: A comparison of algorithm and human performance" ppt
... the 15 texts we selected ranged from 130 to 901 words (5 to 47 sentences); average text length was 442 words (20 sentences), median was 368 words (16 sentences). Additionally, texts were selected ... approaches to sentence ranking against human sentence rankings. To obtain human sentence rankings, we asked people to read 15 texts from the Wall Street Journal on a wide variety of topics (e.g. ... dsij is the tf.idf weight of sentence i in document j, nsi is the number of words in sentence i, k is the kth word in sentence i, tfjk is the frequency of word k in document j, nd is...
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Tài liệu Báo cáo khoa học: "Semi-supervised latent variable models for sentence-level sentiment analysis" pdf
... fine-grained (sentence) sentiment arelearned and inferred jointly. They showed that learn-ing both levels jointly improved performance at bothlevels, compared to learning each level individually,as ... experimentallythat both variants give significantly improvedresults for sentence- level sentiment analysiscompared to all baselines.1 Sentence- level sentiment analysisIn this paper, we demonstrate how combiningcoarse-grained ... bene-fits sentence- level sentiment analysis – an importanttask in the field of opinion classification and retrieval(Pang and Lee, 2008). Typical supervised learning ap-proaches to sentence- level...
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Tài liệu Báo cáo khoa học: "Automatic Evaluation of Sentence-Level Fluency Andrew Mutton∗" pdf
... that a word in the source text will be in the summary, anda language model.Evaluation methods can be said to fall into two cate-gories: a comparison to gold reference, or an appeal to human ... we looked only at sentences generated withseveral parameters fixed, such as sentence length,due to our limited pool of judges. In future we wouldlike to examine the space of sentence types morefully. ... generating ‘sentences’ of a fixedlength is to take word sequences of different lengthsfrom a corpus and glue them together probabilisti-cally: the intuition is that a few longer sequencesglued together...
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Tài liệu Báo cáo khoa học: "A Word-to-Word Model of Translational Equivalence" pptx
... refusal to link content words with function words. Usually, this is the desired behavior, but words like English auxiliary verbs are sometimes used as content words, giving rise to content words ... classifies each word token, for example using a part-of-speech tagger, instead of assigning the same class to all tokens of a given type. The bitext pre- processor for our word- to -word model split ... only one evaluator. Nevertheless, it ap- pears that our word- to -word model with only two link classes does not perform any worse than IBM's Model 2, even though the word- to -word model was...
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Báo cáo khoa học: "A Two-step Approach to Sentence Compression of Spoken Utterances" pdf
... incomplete words areremoved before annotation. In the first step, 8 anno-tators were asked to select words to be removed to compress the sentences. In the second step, 6 an-notators (different ... thecompressed sentence, instead of using the labelsprovided by annotators. This is because when thereare repeated words, annotators sometimes randomlypick removed ones. However, we want to keep ... Each sentence with n words can be viewed asa word sequence X1, X2, , Xn, and our task is to find the best label sequence Y1, Y2, , Ynwhere Yiis one of the three labels. Similar to...
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Báo cáo khoa học: "Bayesian Synchronous Tree-Substitution Grammar Induction and its Application to Sentence Compression" pdf
... resorting to heuris-tics such as minimality of rules, and leading to 1Throughout the paper we will use the word STSG to re-fer to the tree -to- tree version of the formalism, although thestring -to- tree ... rulec → e, and K is the total number of ways to rewrite c, we now take into account ourDP(αc, P0(· | c)) prior in (1), which, whentruncated to a finite grammar, reduces to aK-dimensional Dirichlet ... order-preserving subset ofthe words in the sentence are selected to form thesummary, that is, we summarize by deleting words(Knight and Marcu, 2002). An example sentence pair, which we use as...
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Báo cáo khoa học: "A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation" ppt
... metrics are thenapplied to three new datasets: NIST 2002 ChineseMT Evaluation (3 systems, 2634 sentences total),NIST 2003 Arabic MT Evaluation (2 systems, 1326sentences total), and NIST 2004 ... Head -Word ChainMetric (HWCM) over dependency parse trees.With this wide array of metrics to choose from,MT developers need a way to evaluate them. Onepossibility is to examine whether the automatic ... include sentences fromhigher-quality systems. Consider, for example, thedifferences between R03-all and R03-Top5 versusthe differences between R03-all and R03-Bottom5.Both R03-Top5 and R03-Bottom5...
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Báo cáo khoa học: "A STOCHASTIC APPROACH TO SENTENCE PARSING" pptx
... constraints are known to be indispensable and are recommended to be represented in some formal way and to be referred to during or after the syntac- tic analysis process. However, to represent semantic ... Berenek end Newman 19 A STOCHASTIC APPROACH TO SENTENCE PARSING Tetsunosuke FuJisaki Science Institute, IBM Japan, Ltd. No. 36 Kowa Building 5-19 Sanbancho,Chiyoda-ku Tokyo 102, Japan ABSTRACT ... Magazine 63 Number of sentences checked manually Number of sentences 4 with no correct parse I ~umber of sentences 54 which got highest prob. on most natural parse Number of sentences 5 which...
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Báo cáo khoa học: "Computational Approaches to Sentence Completion" docx
... updated ateach sentence position t. These activations encapsu-late the sentence history up to the tth word in a real-valued vector which typically has several hundreddimensions. The word at position ... combination has three in-puts: the total word similarity, the cosine similaritybetween the sum of the answer word vectors and thesum of the rest of sentence s word vectors, and thenumber of out-of-vocabulary ... =x·yxy.4.1 Total Word SimilarityPerhaps the simplest way of doing sentence comple-tion with LSA is to compute the total similarity of apotential answer a with the rest of the words in thesentence...
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Báo cáo khoa học: "Revision Learning and its Application to Part-of-Speech Tagging" pptx
... classificationproblem, because words in a sentence are notseparated by spaces in Japanese and the mor-phological analyzer has to segment the sentence into words as well as to decide the POS tag ofthe words. So ... Process-ing Based on Stochastic Models. Kyoto University,Doctoral Thesis. (in Japanese).Tetsuji Nakagawa, Taku Kudoh, and Yuji Mat-sumoto. 2001. Unknown Word Guessing andPart-of-Speech Tagging Using ... the training dataso as to make SVMs to learn about unknownwords. The results are shown in Table 1 (row“cutoff-1”). Such procedure improves the accu-racies for unknown words.One advantage of...
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quant 700 to 800 level questions
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- microsoft word 2010 – level 3
- a stochastic approach to sentence parsing
- and coherencebased approaches to sentence ranking
- a bottomup approach to sentence ordering
- automatic mt evaluation at the sentence level
- regression for sentence level mt evaluation with pseudo references
- statistical machine translation with word and sentence aligned parallel corpora
- a hybrid approach to word segmentation and pos tagging
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