teacher in class for 6 8 years old students
Promoting learner autonomy in learning vocabulary for second-year students at Hai Phong Medical University = Phát huy tính tự chủ trong việc học từ vựng cho sin
... processes information." These definitions have the root in cognitive science, with its essential assumption that learning involves information processing In a similar vein, Rubin (1 987 : 29) views ... strategy training Evaluating and revising the strategy training Cohen (19 98) emphasizes that an integral part of the strategy training is ongoing evaluation and revision The training program ... Vocabulary-recording Affix-studying Before training After training 45 Obviously, the frequency mean of each strategy set after the training was higher than that before the training It implies that the students...
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FOCUS ON - pronunciation of three-word phrasal verbs
... lying again, and let out a sigh The lion let out a loud roar before he attacked the hunter Infinitive present tense point out point out & points out -ing form past tense past participle pointing ... pointing out pointed out pointed out point out p.v When you bring things or people to someone's attention or indicate the location of things or people with your hand or index finger, you point them ... participle hold up & holds up holding up held up held up hold up hold up p.v When a wall, column, or other structure supports the weight of something above it, such as a ceiling, it holds it up...
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FOCUS ON - three-word phrasal verbs
... going along with any changes that will mean longer hours for less money Infinitive present tense -ing form past tense past participle go in for go in for & goes in for going in for went in for ... too start planning for retirement point to point to & points to pointing to pointed to pointed to point to p.v When you indicate people or things with your hand or a finger, you point to them When ... pretty bad for a while, but things are starting to look up I'm much happier than I was last year Things are looking up pay for pay for & pays for paying for paid for paid for pay for p.v When...
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three-word phrasal verbs
... going along with any changes that will mean longer hours for less money Infinitive present tense -ing form past tense past participle go in for go in for & goes in for going in for went in for ... too start planning for retirement point to point to & points to pointing to pointed to pointed to point to p.v When you indicate people or things with your hand or a finger, you point to them When ... pretty bad for a while, but things are starting to look up I'm much happier than I was last year Things are looking up pay for pay for & pays for paying for paid for paid for pay for p.v When...
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Learning express Goof Proof Spelling - WORD BASICS
... meteorologist called for intermittent / intramittent rain G Suffixes There are three main groups of suffixes—those for nouns, for adjectives, and for verbs They are listed with their meanings here w ... la / ble Breaking words into their syllables can be helpful in sounding words out, and in managing long or unfamiliar words Often, long words can seem intimidating When broken into smaller syllables, ... bigotry ADJECTIVE ENDINGS SUFFIX MEANING EXAMPLE -able -ian capable, able one who is or does -ic -ile -ious -ive -less causing, making pertaining to having the quality of having the nature of without...
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Tài liệu Báo cáo khoa học: "Word representations: A simple and general method for semi-supervised learning" doc
... 92. 46 92.52 92. 56 92.79 92.91 92. 98 93.25 93.15 93 .66 94. 48 93.17 93.95 - Test 84 .39 86 . 52 88 .13 87 . 36 87 .93 88 .52 87 . 96 88 . 56 88 .93 89 .31 89 .35 88 .88 89 .41 88 .44 89 .31 89 . 36 89 .92 90.04 90. 36 ... 90. 36 90.90 MUC7 67 . 48 71 .80 75.25 77. 76 75.74 78. 84 75.51 78 .64 77 .85 80 .13 79.29 81 .44 82 .71 82 .50 84 .15 - Table 3: Final NER F1 results, showing the cumulative effect of adding word representations, ... (20 08) and HLBL embeddings of various dimensionality, that all curves had similar shapes and optima This is one contributions of our 390 Dev 94. 16 94 .63 94 .66 94 .67 94 .62 94 . 68 94.72 94. 76 -...
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Tài liệu Báo cáo khoa học: "Learning Word-Class Lattices for Definition and Hypernym Extraction" doc
... 99 .88 98. 81 86 . 74 66 .70 50.00 R 42.09 60 .74 66 .14 82 .70 50.00 F1 59.22 75.23 75.05 73 .84 50.00 A 76. 06 83 . 48 81 .84 75 .80 50.00 Algorithm WCL-1 WCL-3 Star patterns Bigrams Random BL Table 2: Performance ... and of the adjective in the second) the annotator selected respec- Full 86 . 19 (2 06) 89 .27 ( 383 ) 65 . 26 (62 ) Substring 96. 23 (230) 96. 27 (413) 88 .42 (84 ) Table 5: Precision in hypernym extraction ... discovery In Proceedings of the 2009 AAAI Spring Symposium on Learning by Reading and Learning to Read, pages 88 –93 Horacio Saggion 2004 Identifying denitions in text collections for question answering...
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Tài liệu Báo cáo khoa học: "Learning Word Vectors for Sentiment Analysis" ppt
... Words (bnc) 85 .45 85 .80 66 .70 84 .55 87 .10 84 .65 87 .05 88 .30 87 .85 88 .90 87 .80 88 .23 67 .42 83 . 96 87 .30 87 .44 87 .99 88 . 28 88. 33 88 .89 87 .77 85 .65 66 .65 82 .82 86 . 65 86 . 19 87 .22 88 . 58 88. 45 88 .13 Bag ... modelling In Proceedings of the ICML, pages 64 1 64 8 G Paltoglou and M Thelwall 2010 A study of information retrieval weighting schemes for sentiment analysis In Proceedings of the ACL, pages 13 86 1395 ... 1371–13 76 C Lin and Y He 2009 Joint sentiment/topic model for sentiment analysis In Proceeding of the 18th ACM Conference on Information and Knowledge Management, pages 375– 384 J Martineau and T Finin...
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Tài liệu Báo cáo khoa học: "Learning Sub-Word Units for Open Vocabulary Speech Recognition" doc
... System Baseline (5k) This Paper (5k) Baseline (10k) This Paper (10k) Hits 18. 25 26. 78 24. 26 28. 96 FAs 1.49 1. 78 1 .82 1.92 Table 1: Coverage of OOV regions by baseline and proposed sub-words in OOVCORP ... Hybrid: Baseline (5k) Hybrid: Baseline (10k) Hybrid: This Paper (5k) Hybrid: This Paper (10k) OOV 1 .62 1. 56 1.51 1.52 1.45 IV 6. 42 6. 44 6. 41 6. 42 6. 39 All 8. 04 8. 01 7.92 7.94 7 .85 Table 2: Phone ... iterations for learning and 200 samples to compute the expectations in Eq The sampler was initialized by sampling for 500 iterations with deterministic annealing for a temperature varying from...
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Tài liệu Báo cáo khoa học: "Learning Word Senses With Feature Selection and Order Identification Capabilities" pdf
... all 18 100 100 133 145 64 100 157 190 200 39 100 183 263 351 22 100 188 255 320 6. 4495 0.40 18 0.1 362 0.0997 0.0937 1. 969 7 0.3234 0.15 58 0.1230 0.1 163 4.2 089 0. 462 8 0.1 488 0.10 16 0.0730 6. 8 169 0.5057 ... 0.25 26 0.19 28 0. 181 1 4.2 089 0 . 68 95 0.2301 0.14 98 0.1059 6. 8 169 0.7045 0.2 763 0.1901 0.1490 Size of feature subset of FSGMM 14 80 80 102 107 55 89 124 1 38 140 32 84 1 28 163 192 20 85 164 225 244 ... 0.20 78 0.1503 0.1149 Size of feature subset of FSGMM 14 80 80 102 107 55 89 124 1 38 140 32 84 1 28 163 192 20 85 164 225 244 MI ×10−2 8. 1070 0.4300 0.14 16 0.1003 0. 089 0 2. 063 9 0.3355 0.1531 0.1 267 ...
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Báo cáo khoa học: "Dealing with Spurious Ambiguity in Learning ITG-based Word Alignment" pdf
... In HLTNAACL Shujie Liu, Chi-Ho Li, and Ming Zhou 2010 Discriminative pruning for discriminative itg alignment In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ... alignments with supervised itg models In Association for Computational Linguistics, Singapore Lauri Karttunen 19 86 Radical lexicalism Technical Report CSLI- 86 - 68, Stanford University Philipp Koehn, ... Yoram Singer 20 06 Online passiveaggressive algorithms J Mach Learn Res., 7:551– 585 , December Jason Eisner 19 96 Efficient normal-form parsing for combinatory categorial grammar In Proceedings of...
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Báo cáo khoa học: "Unsupervised Learning of Acoustic Sub-word Units" pot
... big gain in computational effort5 ML-SSS with ∆=1 was impractical beyond N =22 # of states 10 22 40 SSS (∆ = 1) -7.14 -7. 08 -6. 78 N/A ∆=3 -7.13 -7. 06 -6. 76 -6. 23 ∆=N -7.13 -7. 06 N/A -6. 20 HMM ... states 70 states 3 76 states Table 1: Aggressive state splitting does not cause any degradation in log-likelihood relative to ML-SSS 4.2 24 70.9% 84 .7% 86 . 8% 19 min 60 .2% 75 .8% 76. 6% Table 2: Phone ... training speech for ML-SSS and our procedure The results validate our modifications, demonstrating that at least in the regimes feasible for ML-SSS, there is no loss (in fact a tiny gain) in fitting...
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Báo cáo khoa học: "Learning Expressive Models for Word Sense Disambiguation" pot
... Naïve Bayes 0 .82 0 .61 0. 46 0.74 0 .66 0 .64 0 .81 0 .60 0.50 0 .66 0 .65 SVM Aleph 0 .88 0 . 68 0.47 0.74 0 .66 0.73 0 .83 0 .64 0.51 0 . 68 0 . 68 0.92 0.73 0.49 0.74 0 .66 0 .87 0.93 0 . 68 0.59 0 .82 0.74 Table ... experiments 46 Verb Majority sense 0 . 68 ask 0. 46 come 0.03 get 0.72 give 0.49 go 0.71 live 0. 48 look 0 .64 make 0.14 take 0 .65 tell Average 0.50 C4.5 0 . 68 0.57 0.25 0.71 0 .61 0.72 0 .69 0 .62 0.41 0 .67 0.59 ... there, be) … KS8 The sense with the highest count of overlapping words in its dictionary definition and in the sentence containing the target verb (excluding stop words) (Lesk, 19 86 ) , represented...
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Báo cáo khoa học: "Domain Adaptation with Active Learning for Word Sense Disambiguation" pdf
... 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 a-c-estPred a-truePred a-estPred a r 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 ... 72 70 68 66 64 62 60 58 56 54 52 50 48 46 44 a-truePrior a-truePred a 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Percentage of adaptation examples added (%) Figure 3: Using true ... Results For each adaptation experiment, we start off with a classifier built from an initial training set consisting 76 74 WSD Accuracy (%) 72 70 68 66 64 62 60 58 a-c a r a-truePrior 56 54 52...
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Báo cáo khoa học: " Word Sense Disambiguation in Untagged Text based on Term Weight Learning" ppt
... 597 155 (82 .8) 253 2 18( 86 . 1) 85 9 567 184 (82 .8) 1 78 154( 86 . 5) 762 513 229(75 .8) 424 365 ( 86 . 2) 732 435 145 (66 .8) 374 302 (80 .9) 783 555 1 78( 78. 4) 435 370 (85 .2) 9 96 560 181 (79.7) 2 58 214 (83 .2) 2,742 ... 432 180 (75.0) 124 99(79.9) 727 450 280 ( 76. 7) 240 193 (80 .4) 527 467 270 (80 .8) 187 152 (81 .4) 903 65 1 241(77.7) 372 305 (82 .0) 81 2 65 1 187 (80 .6) 311 255 (82 .3) 711 414 1 98( 71.7) 372 294(79.1) 1, 785 ... 2 76 (27) {see, look, know, feel} 3 18 1 28( 40.2) 162 (50.9) ( 28) {want, desire, search, lack} 267 66 (24.7) 88 (32.0) 28( 8.9~ 53t19 .8) 1 48( 55.5) (29) {lead, cause, guide, precede} 183 139(75.9) 38( 20.7)...
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Báo cáo khoa học: "Transfer Learning, Feature Selection and Word Sense Disambguation" doc
... Setting 85 .75 83 .50 83 .77 85 .94 76. 59 Setting 85 .11 83 .09 83 .44 85 .00 77.14 This paper presented a Transfer Learning formulation which learns a prior suggesting which features are most useful for ... JMLR, 6: 181 7– 185 3 R Ando 20 06 Applying alternating structure optimization to word sense disambiguation In (CoNLL) R Florian and D Yarowsky 2002 Modeling consensus: classifier combination for word ... the training data word_added pos_vbd morph_normal In light of above, the coding scheme, which insubj_use subjsyn_ 169 93 dobj_money corporates the prior information about the predicdobjsyn_ 169 93...
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Báo cáo khoa học: "Robust Word Sense Translation by EM Learning of Frame Semantics" docx
... could HOLD the man for questioning for up to 48 hours before seeking the permission of magistrates for an extension ##HOLD,detaining # 召开,engage|从事-# 牵,guide|引导-# 以为,regard|认为-# 束缚,restrain|制止-# ... tie.v,cause_confinement -> 拘束.v,restrain|制止 tie.v,cognitive_connection -> 联结.v,connect|连 接 Number of frames/senses in FrameNet 6 5 5 5 5 .6 Sense translation accuracy 64 % 100% 55% 88 % 81 % 100% 100% 91% 85 % 76% ... Using Web Data and the EM Algorithm In COLING 2002 Taipei, 2002 Jinying Chen and Martha Palmer (2004) Chinese Verb Sense Discrimination Using EM Clustering Model with Rich Linguistic Features In...
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Báo cáo khoa học: "An Empirical Study of Active Learning with Support Vector Machines for Japanese Word Segmentation" pptx
... 313 62 5 1250 2500 5000 10000 20000 # of Examples 81 3 1525 3 189 61 67 122 18 24 488 487 01 97349 194 785 387 345 7 765 86 # of Binary Features 58 96 10224 1 86 7 2 322 58 562 02 98 561 1 68 4 78 28 86 9 7 493942 82 7023 ... Sent Sent 89 .07 89 .07 90 .89 90 .61 93.11 92.42 94.23 93.53 95.42 94 .82 96. 20 95 .80 96. 51 96. 62 0.95 0.94 Accuracy # of Ex 81 3 181 3 381 3 68 13 1 281 3 2 481 3 488 13 0.93 0.92 0.91 0.9 0 .89 0 .88 10000 ... Active Learning Algorithms 0. 98 0.97 0. 96 Algo A 89 .07 91.70 93 .82 94 .62 95.24 95. 98 96. 51 Algo B 89 .07 91.70 93 .82 94.93 95 .87 96. 43 96. 88 1250 Sent 89 .07 91. 48 93 .60 94.90 95.29 95. 46 Pool Size...
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Báo cáo khoa học: "Fast Online Training with Frequency-Adaptive Learning Rates for Chinese Word Segmentation and New Word Detection" docx
... 5.2e3 5.2e3 1.2e3 NWD Rec 72 .6 75.3 78. 2 77.5 68 .5 68 .0 68 .8 68 .8 77.2 78. 4 79.1 78. 4 Pre 96. 3 97.2 97.5 97 .6 94.0 94.4 94 .8 94 .8 95.0 95.5 95 .8 95 .8 Rec 95.9 97.0 96. 9 97.2 93.9 94.5 94.5 94.7 ... training method is based on feature frequency adaptation, and there is no prior work on using feature frequency information for accelerating online training Other online training methods includes ... models for segmenting and labeling sequence data In 261 Proceedings of the 18th International Conference on Machine Learning (ICML’01), pages 282 – 289 Noboru Murata 19 98 A statistical study of on-line...
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Báo cáo khoa học: "A Combination of Active Learning and Semi-supervised Learning Starting with Positive and Unlabeled Examples for Word Sense Disambiguation: An Empirical Study on Japanese Web Search Query" pdf
... (percentage in trainig set) 3 16 (6. 5%) 64 (4.5%) 86 (4 .6% ) 380 (20.9%) The threshold value in figure is set to empirically optimized value 50 Dependency on threshold value τ will be discussed in 3.3 ... nouns 92 90 88 86 84 τ= 0.0 82 τ= 25.0 80 τ= 50.0 78 τ= 75.0 76 10 20 30 40 50 60 70 80 90 100 Figure 4: Dependency of threshold value τ References Chan, Y S and Ng, H T 2007 Domain Adaptation ... random m-clustering b-clustering 81 66 79 64 77 62 60 75 58 56 Table 1: Selected examples for evaluation 10 20 30 40 50 60 70 80 90 100 Figure 3: Average active learning process Table shows the ambiguous...
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