N-Grams
Correcting Serial Grammatical Errors based on N-grams and Syntax
... combine n-gram statistics from different types of corpora: a Web-scale corpus, a reference corpus, and a learner ...from n-grams of multiple ...
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Towards Arabic Spell Checker Based on N Grams Scores
... The main purpose of this paper is to develop a simple and flexible spell-checker for Arabic language. The proposed spell-checker is based on N-Grams scores. For this purpose, eleven matrices are built to ...
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Not All Character N grams Are Created Equal: A Study in Authorship Attribution
... Character n-grams have been identified as the most successful feature in both single- domain and cross-domain Authorship Attribu- tion (AA), but the reasons for their discrimina- tive value were not fully ...
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The Benefit of Syntactic vs Linear N grams for Linguistic Description
... syntactic n-grams in an authorship attribution task. Their syntactic n- grams include the syntactic relation labels only and achieve good results compared to linear n- ...
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Beyond N Grams: Can Linguistic Sophistication Improve Language Modeling?
... Beyond N Grams Can Linguistic Sophistication Improve Language Modeling? Beyond N Grams Can Linguistic Sophistication Improve Language Modeling? Eric Brill, R a d u F l o r i a n , J o h n C H e n d e[.] ...
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Improving Reordering with Linguistically Informed Bilingual n grams
... Our model obtained slightly higher transla- tion accuracy (BLEU) results. We also analysed the quality of the reorderings output by our sys- tem when performing the new reordering model, which also outperformed the ...
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Composing Simple Image Descriptions using Web scale N grams
... Studying natural language, and especially how people describe the world around them can help us better understand the visual world. In turn, it can also help us in the quest to generate natural language that describes ...
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Local Histograms of Character N grams for Authorship Attribution
... character n-gram representations. However, as with word-based features, character n-grams are unable to incorporate sequential information from documents in their original form (in terms of the ...
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Visual Webpage Content Segmentation and Retrieval Based on n-Grams
... a n-gram based web page segmentation algorithm. That utilized the n-grams for segmenting the webpage without relying on the DOM tree for the segmentation ...
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Comparing Word Relatedness Measures Based on Google n grams
... Islam et al. (2012) used Google n-grams, the Google tri-grams in particular, for determining the similarity of a pair of words. Their tri-gram word relatedness model can be generalized to ...
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Integrating Dictionary and Web N-grams for Chinese Spell Checking
... Our systems were designed to provide wide coverage spell checking for Chinese. As such, we trained our systems using a dictionary, a compiled corpus, and Web scale n-grams. We evaluated our systems on the ...
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Text Segmentation Using N grams to Annotate Hadith Corpus
... into N-grams depending on the technique applied, next each token is labelled as Isnad, Matn or Neither by comparing it with pre-compiled lists obtained from the gold standard created earlier as explained in ...
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Modelling and Optimizing on Syntactic N Grams for Statistical Machine Translation
... counting n-gram matches between the translation output and the reference, it compares head-word chains, or syntactic ...syntactic n-grams from the reference translations of the respective develop- ...
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Converting System of PhoneticsTranscriptionstoMyanmarText Using N-Grams Language Models
... developed n-grams language models from correct training data in Myanmar ...trained n-grams language models, the system can be converted from Phonetics to Myanmar ...trained ...
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Charagram: Embedding Words and Sentences via Character n grams
... The other settings for our models are mostly the same as for the word and sentence experiments (Sec- tion 4.1). We again use character n-grams with n ∈ { 2, 3, 4 }, tuning over whether to include all ...
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Inferring Selectional Preferences from Part Of Speech N grams
... POS N-grams, in order to learn a mapping from POS N-grams to those ...POS N-grams containing particular target and relative words, PONG POS-tags Google N- grams ...
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Native Language Identification Using a Mixture of Character and Word N grams
... Native language identification (NLI) is the task of determining an author’s native lan- guage, based on a piece of his/her writ- ing in a second language. In recent years, NLI has received much attention due to its ...
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Extension of Zipf’s Law to Word and Character N-grams for English and Chinese
... with n-gram words or characters in one list and put in order of frequency, the frequency of tokens in the combined list follows Zipf’s law approximately with the slope close to -1 on a log- log plot for all ...all ...
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New Tools for Web-Scale N-grams
... the N-gram search en- gine system described in (Sekine, ...matching N-grams for this query, and avoids returning N-grams which have a comma or a common noun at the first position or a ...
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The Power of Character N grams in Native Language Identification
... Although countless POS-taggers exist, one ma- jor problem in acquiring reliable tags is intrinsic to the non-native nature of the texts we deal with. As POS models for English are trained on native En- glish data, it is ...
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