Survey on Publicly Available Sinhala Natural Language Processing Tools and Research

N de Silva - arXiv preprint arXiv:1906.02358, 2019

… [21] further provided two monolingual corpora for Sinhala. Those were a 155k+ sentences of filtered Sinhala Wikipedia8 and 5178k+ sentences of Sinhala common crawl9. 2.2 Data Sets Specific data sets for Sinhala, as expected. is scarce …


Synchronous Bidirectional Neural Machine Translation

L Zhou, J Zhang, C Zong - Transactions of the Association for Computational …, 2019

Create a new account. Email. Returning user. Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …


Syntactic dependencies correspond to word pairs with high mutual information

R Futrell, P Qian, E Gibson, E Fedorenko, IA Blank

… 2.5 Dataset We use the Common Crawl corpus (Buck et al., 2014) of English web text … Entropy, 19:275–307. Buck, C., Heafield, K., and Van Ooyen, B. (2014). N-gram counts and language models from the common crawl. In …


Syntactically Supervised Transformers for Faster Neural Machine Translation

N Akoury, K Krishna, M Iyyer - arXiv preprint arXiv:1906.02780, 2019

… For English-German, we evaluate on WMT 2014 En↔De as well as IWSLT 2016 En→De, while for English-French we train on the Europarl / Common Crawl subset of the full WMT 2014 En→Fr data and evaluate over the full dev/test sets …


Syntax-aware Multilingual Semantic Role Labeling

S He, Z Li, H Zhao - arXiv preprint arXiv:1909.00310, 2019

… The pre-trained word em- bedding is 100-dimensional GloVe vectors (Pennington et al., 2014) for English, 300-dimensional fastText vectors (Grave et al., 2018) trained on Common Crawl and Wikipedia for other languages …


Syntax-Aware Sentence Matching with Graph Convolutional Networks

Y Lei, Y Hu, X Wei, L Xing, Q Liu - International Conference on Knowledge Science …, 2019

… 4.2 Experiment Setting. In order to compare with the baseline, we use the same setting as BiMPM. We initialize word embeddings in the word representation layer with the 300-dimensional GloVe word vectors …


N Londhe, S Kannan, N Bojja - US Patent App. 16/272,142, 2019

US20190260694A1 - System and method for chat community question answering - Google Patents. System and method for chat community question answering. Download PDF Info. Publication number US20190260694A1. US20190260694A1 …


System and method for concise display of query results via thumbnails with indicative images and differentiating terms

… grams). In the case of a meta-search engine without access to the underlying indexes, one approach is to use data from the Common Crawl to derive global n-gram counts for TF-IDF and language modeling filtering. Another …


System for creating a reasoning graph and for ranking of its nodes

B Agapiev - US Patent App. 15/793,751, 2019

… View, Calif. and Common Crawl Foundation of Beverly Hills, Calif.) are processed (20) to identify statements of causal relationships (22, 24), which are then analyzed to extract causes and associated effect pairs (26). These …


TüBa-D/DP Stylebook

… Table 1: Subcorpora of the TüBa-D/DP. Subcorpus Genre Sentences Tokens Europarl Parliamentary proceedings 2.2M 55M taz (1986-2009) Newspaper 29.9M 393.7M Wikipedia (2019) Encyclopedia 42.2M …


TabbyXL: Rule-Based Spreadsheet Data Extraction and Transformation

A Shigarov, V Khristyuk, A Mikhailov, V Paramonov - International Conference on …, 2019

… a spreadsheet-like format. Barik et al. [2] extracted 0.25M unique spreadsheets from Common Crawl 1 archive. Chen and Cafarella [6] reported about 0.4M spreadsheets of ClueWeb09 Crawl 2 archive. Spreadsheets can be …


Page 1. Tackling Graphical NLP problems with Graph Recurrent Networks by Linfeng Song Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Supervised by Professor Daniel Gildea Department of Computer Science …


TARGER: Neural Argument Mining at Your Fingertips

A Chernodub, O Oliynyk, P Heidenreich, A Bondarenko…

… Our background collection for the retrieval of argumentative sentences is formed by the DepCC corpus (Panchenko et al., 2018), a linguistically pre-processed subset of the Common Crawl containing 14.3 … Building a …


Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes

JM Steinkamp, W Bala, A Sharma, JJ Kantrowitz - Journal of Biomedical Informatics, 2019

… Our word embeddings consisted of 300-dimensional Global Vectors (GloVe) [35] trained on the web common crawl data set concatenated with 300-dimensional custom trained FastText [28] vectors trained on the entirety …


Team EP at TAC 2018: Automating data extraction in systematic reviews of environmental agents

A Nowak, P Kunstman - arXiv preprint arXiv:1901.02081, 2019

… The model architecture is shown in Figure 3. Embeddings layer: Each token is represented by 1452 dimensional vector, consisting of: • 300-dimensional GloVe (Pennington et al., 2014) embedding (cased, trained on 840B tokens from Common Crawl) …


GE Pibiri, R Venturini - arXiv preprint arXiv:1908.10598, 2019

Page 1. Techniques for Inverted Index Compression GIULIO ERMANNO PIBIRI, ISTI-CNR, Italy ROSSANO VENTURINI, University of Pisa, Italy The data structure at the core of large-scale search engines is the inverted index …


Tell me you can read me

Page 55. Complying with the obligation of transparency imposes indeed on the data controller the prior obligation to determine–deliberately or not, consciously or not–who are the targeted data subjects, and what are they supposed to find intelligible and easily accessible …


Temporal Context-Aware Representation Learning for Question Routing

X Zhang, W Cheng, B Zong, Y Chen, J Xu, D Li…

… The state-of-the-art document embedding model, InferSent [3], is applied to compute the similarity between questions. We use the pre-trained 300-dimensional word vectors from fastText[19], which is trained on Common Crawl containing 600B tokens …


Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction

J Wang, L Ma, W Jiang - arXiv preprint arXiv:1909.05010, 2019

… 2015) features are adopted for all compared methods. Each word from the query is represented by GloVe (Pennington, Socher, and Manning 2014) word embedding vectors pre-trained on Common Crawl. We set hidden neuron size of LSTM to 512 …


Text Classification Using SVM Enhanced by Multithreading and CUDA

S Chatterjee, PG Jose, D Datta - International Journal of Modern Education and …, 2019

Page 1. IJ Modern Education and Computer Science, 2019, 1, 11-23 Published Online January 2019 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijmecs.2019.01.02 Copyright © 2019 MECS IJ Modern Education and Computer Science, 2019, 1, 11-23 …


Text Corpus for NLP

… Sep 2019. Common Crawl publishes 240 TiB of uncompressed data from 2.55 billion web pages. Of these, 1 billion URLs were not present in previous crawls. Common Crawl started in 2008. In 2013, they moved from ARC to Web ARChive (WARC) file format …


TEXT QUALITY EVALUATION METHODS AND PROCESSES

AA Pala, A Kagoshima, M Tober - US Patent App. 15/863,408, 2019

… In one possible implementation, the reference text 2000 can be parts, or the complete version, of Wikipedia, for a given language, or one or more books, or Common Crawl, or any other corpus that consists of human-written high quality text …


The AFRL WMT19 Systems: Old Favorites and New Tricks

J Gwinnup, G Erdmann, T Anderson - Proceedings of the Fourth Conference on …, 2019


The BEA-2019 Shared Task on Grammatical Error Correction

C Bryant, M Felice, ØE Andersen, T Briscoe - … Workshop on Innovative Use of NLP for …, 2019

Page 1. Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 52–75 Florence, Italy, August 2, 2019. c 2019 Association for Computational Linguistics 52 The BEA-2019 …


The BLCU System in the BEA 2019 Shared Task

L Yang, C Wang - Proceedings of the Fourteenth Workshop on Innovative …, 2019

… JunczysDowmunt and Grundkiewicz (2016); JunczysDowmunt et al. (2018) utilize the Common Crawl corpus to train the language model and pre-train part of the NMT model. Inspired by these studies, we also try to use a monolingual corpus for data augmentation …


The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings

AC Kozlowski, M Taddy, JA Evans - American Sociological Review, 2019

We argue word embedding models are a useful tool for the study of culture using a historical analysis of shared understandings of social class as an empirical case. Word embeddings represent semant...


Page 1. The impact of individual audit partners on their clients' narrative disclosures ∗ Christoph Mauritz1, Martin Nienhaus2, and Christopher Oehler2 1University of Münster 2Goethe-University Frankfurt September 5, 2019 Abstract …


The LAIX Systems in the BEA-2019 GEC Shared Task

R Li, C Wang, Y Zha, Y Yu, S Guo, Q Wang, Y Liu… - … on Innovative Use of NLP for …, 2019

… Table 1 lists the data sets used in Restricted Track and Unrestricted Track, including FCE (Yannakoudakis et al., 2011), Lang-82 (Mizumoto et al., 2012), NUCLE (Ng et al., 2014), W&I+LOCNESS (Bryant et al., 2019) and Com …


The LIG system for the English-Czech Text Translation Task of IWSLT 2019

L Vial, B Lecouteux, D Schwab, H Le, L Besacier - arXiv preprint arXiv:1911.02898, 2019

… C is a speech translation corpus of TED talks, similar to the test data of the task, and we added the News Commentary corpus, which consists of political and economic commentaries, be- cause it was the second smallest corpus …


The Linked Open Data cloud is more abstract, flatter and less linked than you may think!

L Asprino, W Beek, P Ciancarini, F van Harmelen… - arXiv preprint arXiv …, 2019

… The two largest available crawls of LOD that are available today are WebDataCommons and LOD-a-lot. WebDataCommons5 [12] consists of ∼31B triples that have been extracted from the CommonCrawl datasets (November 2018 version) …


The NiuTrans Machine Translation Systems for WMT19

B Li, Y Li, C Xu, Y Lin, J Liu, H Liu, Z Wang, Y Zhang…

… For EN↔RU, we used the following resource provided by WMT, including News Commentaryv14, ParaCrawl-v3, CommonCrawl and Yandex … corpus via random samplimng from 2M monolingual data selected by Xenc in the …


The Quest to Automate Fact-checking

… The model contains 300-dimensional vectors for 3 million words and phrases. https://code.google.com/archive/p/word2vec/ 2: Global Vectors for Word Representation using The Common Crawl corpus which contains …


The relationship between implicit intergroup attitudes and beliefs

B Kurdi, TC Mann, TES Charlesworth, MR Banaji - Proceedings of the National …, 2019

Skip to main content. Submit; About: Editorial Board; PNAS Staff; FAQ; Rights and Permissions; Site Map. Contact; Journal Club; Subscribe: Subscription Rates; Subscriptions FAQ; Open Access; Recommend PNAS to Your …


The RWTH Aachen University Machine Translation Systems for WMT 2019

J Rosendahl, C Herold, Y Kim, M Graça, W Wang… - Proceedings of the Fourth …, 2019

… For De→En, we use data from CommonCrawl, Europarl, NewsCommentary and Rapid … (2017)), but without tied embedding weights, on the data from CommonCrawl, Europarl, NewsCommentary and Rapid ie about 6M sentence pairs …


The Semantic Web: Two Decades On


The Source-Target Domain Mismatch Problem in Machine Translation

J Shen, PJ Chen, M Le, J He, J Gu, M Ott, M Auli… - arXiv preprint arXiv …, 2019

… For Myanmar monolingual data, we use the language split Commoncrawl data from (Buck et al., 2014) which includes texts in various domains crawled from the web. We use the myanmar-tools2 library to classify and convert all Zawgyi text to Unicode …


The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT

N Casas, JAR Fonollosa, C Escolano, C Basta… - Proceedings of the Fourth …, 2019

… 4.2 English-Russian The available parallel English-Russian corpora for the shared task included News Commentary v14, Wiki Titles v1, Common Crawl corpus, ParaCrawl v3, Yandex Corpus and the United Nations Parallel Corpus v1.0 (Ziemski et al., 2016) …


The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019

… 556 corpus lang. raw cleaned News Crawl kk 783k 783k Wiki dumps kk 1.7M 1.7M Common Crawl kk 10.9M 5.4M News Crawl en 200M 200M … The same filtering was applied to the monolingual Kazakh Common Crawl corpus …


The University of Helsinki submissions to the WMT19 news translation task

A Talman, U Sulubacak, R Vázquez, Y Scherrer… - arXiv preprint arXiv …, 2019

… removing all sentence pairs with a length difference ratio above a certain threshold: for CommonCrawl, ParaCrawl and Rapid we used a threshold of 3, for WikiTitles a threshold of 2, and for all other data sets a threshold of 9; …


The University of Sydney's Machine Translation System for WMT19

L Ding, D Tao - arXiv preprint arXiv:1907.00494, 2019

… 3 Data Preparation We used all available parallel corpus 3 for Finnish→ English except the “Wiki Headlines” due to the large number of incomplete sentences, and for monolingual target side English data, we selected all …


The Web is missing an essential part of infrastructure: an Open Web Index

D Lewandowski - arXiv preprint arXiv:1903.03846, 2019

… A search engine needs to keep its index current, meaning it needs to update at least a part of it every minute. This is an important requirement that is not being met by any of the current projects (like Common Crawl) …


CX Chu, S Razniewski, G Weikum - arXiv preprint arXiv:1901.10263, 2019

Page 1. TiFi: Taxonomy Induction for Fictional Domains [Extended version] ∗ Cuong Xuan Chu Max Planck Institute for Informatics Saarbrücken, Germany cxchu@mpi-inf. mpg.de Simon Razniewski Max Planck Institute for Informatics …


TLR at BSNLP2019: A Multilingual Named Entity Recognition System

JG Moreno, EL Pontes, M Coustaty, A Doucet - Proceedings of the 7th Workshop on …, 2019

… in Figure 1. 3.1 FastText Embedding In this layer, we used pre-trained embeddings for each language trained on Common Crawl and Wikipedia using fastText (Bojanowski et al., 2017; Grave et al., 2018). These models were …


TMU Transformer System Using BERT for Re-ranking at BEA 2019 Grammatical Error Correction on Restricted Track

M Kaneko, K Hotate, S Katsumata, M Komachi - … Workshop on Innovative Use of NLP …, 2019

… The 5-gram language model for re-ranking was trained on a subset of the Common Crawl corpus (Chollampatt and Ng, 2018a).5 We used a Python spell checker tool6 on the GEC model hy- pothesis sentences. 3.3 Evaluation …


Top-K Attention Mechanism for Complex Dialogue System

… Then, the model submit the candidate with the highest value among the given candidates as the final correct an- swer. They randomly sampled one of the 99 negative samples to prevent bias during learning and used …


Toponym Identification in Epidemiology Articles--A Deep Learning Approach

MR Davari, L Kosseim, TD Bui - arXiv preprint arXiv:1904.11018, 2019

… In order to measure the effect of such domain specific information, we experimented with 2 other pretrained word embedding models: Google News Word2vec [11], and a GloVe Model trained on Common Crawl [24] … Common Crawl GloVe 2.2M 300 29.84 …


Toward Automated Worldwide Monitoring of Network-Level Censorship

Page 1. Toward Automated Worldwide Monitoring of Network-level Censorship Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Zachary Weinberg BA Chemistry, Columbia University …


YT Cao, H Daumé III - arXiv preprint arXiv:1910.13913, 2019

Page 1. Toward Gender-Inclusive Coreference Resolution YANG TRISTA CAO, University of Maryland HAL DAUMÉ III, Microsoft Research & University of Maryland ABSTRACT Correctly resolving textual mentions of people …


Towards a Global Perspective on Web Tracking

N Samarasinghe, M Mannan - Computers & Security, 2019

… Schelter et al. Schelter and Kunegis (2016) performed a large scale analysis of third-party trackers using the Common Crawl 2012 corpus. The corpus may contain tracking information of residential as well as institutional users …


Towards an Automated Extraction of ABAC Constraints from Natural Language Policies

M Alohaly, H Takabi, E Blanco - IFIP International Conference on ICT Systems …, 2019

… model. To configure the model, we set one hyper-parameter value at a time. Our default settings: dropout = 0, decay rate = 0, number of BiLSTM cells (ie, layers) = 1, and GloVe (Common crawl) with 300 dimensions. To determine …


Towards an automated method to assess data portals in the deep web

AS Correa, RM de Souza, FSC da Silva - Government Information Quarterly, 2019


Towards Content Expiry Date Determination: Predicting Validity Periods of Sentences

… For this, we use Common Crawl dataset 16 which is a web dump composed of billions of websites with plain text versions available … For each sentence found in the Common Crawl dataset we identify DATE, TIME and DURATION …


Towards Content Transfer through Grounded Text Generation

S Prabhumoye, C Quirk, M Galley - arXiv preprint arXiv:1905.05293, 2019

05/13/19 - Recent work in neural generation has attracted significant interest in controlling the form of text, such as style, persona, and p...


Towards countering hate speech and personal attack in social media

P Charitidis, S Doropoulos, S Vologiannidis… - arXiv preprint arXiv …, 2019

… each language. After conducting some preliminary experiments, the best pre-trained embedding choice for Greek and French language was using fastText embeddings [45], trained on Common Crawl and Wikipedia. For English …


Towards Functionally Similar Corpus Resources for Translation

… Secondly, we used lemmatised texts, with stop words filtered out (biLSTMlex in Table 1). For both scenarios we used pre-trained word embeddings of size 300, trained on the English Wikipedia and CommonCrawl data, using …


Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning

D Cevher, S Zepf, R Klinger - arXiv preprint arXiv:1909.02764, 2019

… We use a neural network with an embedding layer (frozen weights, pretrained on Common Crawl and Wikipedia (Grave et al., 2018)), a bidirectional LSTM (Schuster and Paliwal, 1997), and two dense layers followed by a soft max output layer …


Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

S Castro, D Hazarika, V Pérez-Rosas, R Zimmermann… - arXiv preprint arXiv …, 2019

… 768. We also considered averaging Common Crawl pre-trained 300 dimensional GloVe word vectors (Pennington et al., 2014) for each token; however, it resulted in lower performance as compared to BERT-based features …


Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation

B Wu, H Zhang, M Li, Z Wang, Q Feng, J Huang… - arXiv preprint arXiv …, 2020

HZ Bowen Wu, M Li, Z Wang, Q Feng, J Huang…

… paper. 4.3 Hyperparameters For the student model in our proposed distilling method, we employ the 300-dimension GloVe (840B Common Crawl version; Pennington et al., 2014) to initialize the word embeddings. The number …


Towards Robust Named Entity Recognition for Historic German

S Schweter, J Baiter - arXiv preprint arXiv:1906.07592, 2019

… 69.59% Common Crawl 68.97% Wikipedia + Common Crawl 72.00% Wikipedia + Common Crawl + Character 74.50 … 69.62% Riedl and Padó (2018) (with transfer-learning) 74.33% ONB Wikipedia 75.80% CommonCrawl 78.70% Wikipedia + CommonCrawl 79.46 …


Towards semantic-rich word embeddings

G Beringer, M Jabłonski, P Januszewski, A Sobecki…

… collected (III), for the our approach. We use a pretrained embedding model from spaCy - en_vectors_web_lg, which contains 300-dimensional word vectors trained on Common Crawl with GloVe2. We compare results on the …


Towards Unsupervised Grammatical Error Correction using Statistical Machine Translation with Synthetic Comparable Corpus

S Katsumata, M Komachi - arXiv preprint arXiv:1907.09724, 2019

… makes up for the synthetic target data. To compare the fluency, the outputs of each best iter on JFLEG were evaluated with the perplexity based on the Common Crawl language model10. The perplexity of USMTforward in iter …


Tracking Naturalistic Linguistic Predictions with Deep Neural Language Models

M Heilbron, B Ehinger, P Hagoort, FP de Lange - arXiv preprint arXiv:1909.04400, 2019

… Non-predictive controls We included two non-predictive and potentially confounding variables: first, frequency which we quantified as unigram surprise (−log p(w)) which was based on a word's lemma count in the CommonCrawl corpus, obtained via spaCy …


Transfer Learning across Languages from Someone Else's NMT Model

T Kocmi, O Bojar - arXiv preprint arXiv:1909.10955, 2019

… WMT 2012 WMT 2018 English - French Commoncrawl, Europarl, Giga FREN, News commentary, UN corpus WMT 2013 WMT dis. 2015 … Based on our previous experiments, we ex- clude the noisiest corpus, ie web crawled ParaCrawl or Commoncrawl …


Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task

V Slovikovskaya - arXiv preprint arXiv:1910.14353, 2019

… 9XLNet is named after TransformerXL 10These corpora include (1) BOOK CORPUS [Zhu et al., 2015] plus English Wikipedia, the original data used to train BERT (16GB); (2) CC-NEWS, which authors collected from the English …


Transforma at SemEval-2019 Task 6: Offensive Language Analysis using Deep Learning Architecture

R Ong - arXiv preprint arXiv:1903.05280, 2019

… This allows us to evaluate the increase in di- mensionality on the performance of our models 3. GloVe: Common Crawl (300d) - Trained on 42B tokens, 1.9M vocabulary of unique words … Table 7: T - GloVe Twitter, CC - GloVe Common Crawl …


transformers. zip: Compressing Transformers with Pruning and Quantization

… 9: return M 4 Page 5. 4 Experiments 4.1 Dataset We train and evaluate on the WMT English - German translation task. Specifically, we train on all of Europarl, Common Crawl, and News Commentary, validate on the …


Translating Translationese: A Two-Step Approach to Unsupervised Machine Translation

N Pourdamghani, N Aldarrab, M Ghazvininejad…

… For Arabic we use MultiUN (Tiedemann, 2012). For French we use CommonCrawl For German we use a mix of CommonCrawl (1.7M), and NewsCommentary (300K) … For Spanish we use CommonCrawl (1.8M), and Europarl (200K) …


Deep Learning Monitor. Paper Detail. Close This Page. Tree Edit Distance Learning via Adaptive Symbol Embeddings. 2018-06-18 13:54:45; Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer; 0. Abstract …


TU Wien@ TREC Deep Learning'19--Simple Contextualization for Re-ranking

S Hofstätter, M Zlabinger, A Hanbury - arXiv preprint arXiv:1912.01385, 2019

… For the full task we generated initial rankings with Anserini using BM25 and utilized the validation sets to tune the re-ranking 1https://github.com/microsoft/BlingFire 242B CommonCrawl lower-cased: https://nlp.stanford.edu/projects/glove …


Twitter Sentiment on Affordable Care Act using Score Embedding

M Farhadloo - arXiv preprint arXiv:1908.07061, 2019

… The embeddings pre-trained on Common Crawl data were only available in dimension 300 and were trained on 840 billion tokens with vocabulary … of available unlabeled training data had an impact on the performance …


Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English

F Guzmán, PJ Chen, M Ott, J Pino, G Lample, P Koehn… - arXiv preprint arXiv …, 2019

… M monolingual Wikipedia (en) 67.8M 2.0B Common Crawl (ne) 3.6M 103.0M Wikipedia (ne) 92.3K 2.8M Sinhala–English … 5M monolingual Wikipedia (en) 67.8M 2.0B Common Crawl (si) 5.2M 110.3M Wikipedia (si) 155.9K 4.7M …


Type: Report Dissemination level: Public Due Date (in months): 24 (August 2019)

Page 1. X Modal X Cultural X Lingual X Domain X Site Global OER Network Grant Agreement Number: 761758 Project Acronym: X5GON Project title: Cross Modal, Cross Cultural, Cross Lingual, Cross Domain, and Cross Site …


UdS-DFKI Participation at WMT 2019: Low-Resource (en-gu) and Coreference-Aware (en-de) Systems

C España-Bonet, D Ruiter - Proceedings of the Fourth Conference on Machine …, 2019

… proportions. Our base system uses CommonCrawl … x1 Parallel CommonCrawl 2,394,878 x1 x4 Europarl 1,775,445 x1 x4 NewsCommentary 328,059 x4 x16 Rapid 1,105,651 x1 x4 ParaCrawlFiltered 12,424,790 x0 x1 Table …


Understanding and Mitigating the Security Risks of Content Inclusion in Web Browsers

… 47 5.1 Sample URL grouping. . . . . 73 5.2 Narrowing down the Common Crawl to the candidate set used in our analysis (from left to right) . . . . 79 5.3 Vulnerable pages and sites in the candidate set …


Uni-and Multimodal and Structured Representations for Modeling Frame Semantics

Page 1. Uniand Multimodal and Structured Representations for Modeling Frame Semantics Vom Fachbereich Informatik der Technischen Universität Darmstadt genehmigte Dissertation zur Erlangung des akademischen Grades …


H Wu, J Mao, Y Zhang, Y Jiang, L Li, W Sun, WY Ma - arXiv preprint arXiv:1904.05521, 2019

Page 1. Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations Hao Wu1,3,4,6,∗,†, Jiayuan Mao5,6,∗,†, Yufeng Zhang2,6,†, Yuning Jiang6, Lei Li6, Weiwei Sun1,3,4, Wei-Ying Ma6 …


Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition

WF Chen, K Al-Khatib, M Hagen, H Wachsmuth…

… The hidden state is employed to predict the probability of 'not-attack' using a linear regression layer. We use 300-dimensional word embeddings (Pennington et al., 2014) pre-trained on the Common Crawl with 840 …


Unsupervised Cross-lingual Representation Learning at Scale

A Conneau, K Khandelwal, N Goyal, V Chaudhary… - arXiv preprint arXiv …, 2019

… As shown in Figure 1, the CommonCrawl Corpus that we collected has significantly more monolingual data than the previously used Wikipedia corpora. Figure 3 shows that for the same BERTBase architecture, all models …


Unsupervised Extraction of Partial Translations for Neural Machine Translation

B Marie, A Fujita - Proceedings of the 2019 Conference of the North …, 2019

… We extracted monolingual data ourselves from the Common Crawl project8 for Bengali (5.3M lines) and Malay (4.6M lines … 8http://commoncrawl org/ 9https://fasttext.cc/ 10The extraction of 100k partial translations from …


Unsupervised Joint Training of Bilingual Word Embeddings

B Marie, A Fujita - Proceedings of the 57th Conference of the Association …, 2019

… For en- id, we used English (100M lines) and Indonesian (77M lines) Common Crawl corpora.5 We then mapped the word embeddings into a BWE space using VECMAP,6 one of the best and most robust methods for unsupervised mapping (Glavas et al., 2019) …


Unsupervised Lemmatization as Embeddings-Based Word Clustering

R Rosa, Z Žabokrtský - arXiv preprint arXiv:1908.08528, 2019

… For the experiments reported in this paper, we use the pretrained word embedding dictionaries available from the FastText website.78 The word embeddings had been trained on Wikipedia9 and Common Crawl10 texts …


Unsupervised Question Answering by Cloze Translation

P Lewis, L Denoyer, S Riedel - arXiv preprint arXiv:1906.04980, 2019

… Question Corpus We mine questions from En- glish pages from a recent dump of common crawl using simple selection criteria:3 We select sen … 3http:// commoncrawl.org/ 4We also experimented with language model pretraining …


Updating Pre-trained Word Vectors and Text Classifiers using Monolingual Alignment

P Bojanowski, O Celebi, T Mikolov, E Grave, A Joulin - arXiv preprint arXiv …, 2019

… Indeed, despite their size, large web data such as Common Crawl lack coverage for highly technical expert fields such as medicine or law … Training data. We take two subsets of the May 2017 dump of the Common Crawl …


Updating verbal fluency analysis for the 21st century: Applications for psychiatry

TB Holmlund, J Cheng, PW Foltz, AS Cohen, B Elvevåg - Psychiatry Research, 2019

… To base the analysis on a corpus with a wide variety of animal-word sources, we used a set of pre-trained word vectors calculated from approximately 42 billion tokens from the entire internet, courtesy of the Common Crawl project (Pennington et al., 2014) …


Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs

A Fan, C Gardent, C Braud, A Bordes - 2019

… WikiSum Second, we experiment on the WikiSum CommonCrawl (Liu et al., 2018b) summarization dataset4 with 1.5 million examples … denotes results from (Liu et al., 2018b) that use data scraped from unrestricted web search, not the static CommonCrawl version …


T Gröndahl, N Asokan - arXiv preprint arXiv:1902.09381, 2019

Page 1. arXiv:1902.09381v1 [cs.CL] 25 Feb 2019 Using logical form encodings for unsupervised linguistic transformation: Theory and applications Tommi Gröndahl N. Asokan Abstract We present a novel method to architect …


Using the Semantic Web as a source of training data

C Bizer, A Primpeli, R Peeters - Datenbank-Spektrum, 2019

… The Web Data Commons (WDC) project 4 monitors the adoption of schema.org annotations on the Web by analysing the Common Crawl 5 , a series of public web corpora each containing several billion HTML pages [12]. The …


Using Whole Document Context in Neural Machine Translation

V Macé, C Servan - arXiv preprint arXiv:1910.07481, 2019

… models are evaluated on the same standard corpora that have Page 3. Corpora #lines # EN # DE Common Crawl 2.2M 54M 50M Europarl V9† 1.8M 50M 48M News Comm. V14† 338K 8.2M 8.3M ParaCrawl V3 27.5M 569M …


Variational Auto-Decoder: Neural Generative Modeling from Partial Data

A Zadeh, YC Lim, PP Liang, LP Morency - arXiv preprint arXiv:1903.00840, 2019

… CMU-MOSEI consists of 23,500 sentences and CMU-MOSI consists of 2199 sentences. For text modality, the datasets contain GloVe word embeddings (Pennington et al., 2014) trained on 840 billion tokens from the Common Crawl dataset …


Vernon-fenwick at SemEval-2019 Task 4: Hyperpartisan News Detection using Lexical and Semantic Features

V Srivastava, A Gupta, D Prakash, SK Sahoo, RR Rohit… - Proceedings of the 13th …, 2019

… semantic space. We have used 300-dimensional Glove embeddings trained on Common Crawl data of 2.2 million words and 840 billion tokens. An ar- ticle was tokenized into sentences and further into words to obtain it's article representation …


Y Jang, Y Song, CD Kim, Y Yu, Y Kim, G Kim - International Journal of Computer …, 2019

Page 1. International Journal of Computer Vision https://doi.org/10.1007/s11263-01901189-x Video Question Answering with Spatio-Temporal Reasoning Yunseok Jang1 · Yale Song2 · Chris Dongjoo Kim1 · Youngjae Yu1 · Youngjin Kim1 · Gunhee Kim1 …


Vir is to Moderatus as Mulier is to Intemperans Lemma Embeddings for Latin

… Both Facebook and the organizers of the CoNLL shared tasks on multilingual parsing have pre-computed and released word embeddings trained on Latin texts crawled from the web: the former using the fastText model on …


Vision-based Page Rank Estimation with Graph Networks

… The Open PageRank initiative provides freely available data that was built on top of Common Crawl [do/19], which provides high quality crawl data of webp ages since 2013. Open PageRank uses the number of backlinks of …


VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository

K Hu, N Gaikwad, M Bakker, M Hulsebos, E Zgraggen…

… Corpora The first category of corpora includes data tables harvested from the web. In particular, we use horizontal relational tables from the WebTables 2015 corpus [6], which extracts structured tables from the Common Crawl …


Wanca in Korp: Text corpora for underresourced Uralic languages

H Jauhiainen, T Jauhiainen, K Lindén - DATA AND HUMANITIES (RDHUM) 2019 …

… In addition to conducting our own crawling, we also used the pre-crawled corpus distributed by the Common Crawl Foundation … 2 In addition to conducting our own crawling, we used the pre-crawled corpus distributed by the Common Crawl Foundation …


WDC Product Data Corpus and Gold Standard for Large-Scale Product Matching-Version 2.0

… methods. The Web Data Commons project regularly extracts schema.org annotations from the Common Crawl, a large public web corpus. November 2017 version of the WDC schema.org data set contains 365 million offers …


Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings

H Wang, J Henderson, P Merlo - arXiv preprint arXiv:1904.09446, 2019

… (2018a)11, we use their pretrained CBOW embeddings of 300 dimensions. For English, Italian and German, the models are trained on the WacKy corpus. The Finnish model is trained from Common Crawl and the Spanish model is trained from WMT News Crawl …


Web Archive Analysis Using Hive and SparkSQL

X Wang, Z Xie - 2019 ACM/IEEE Joint Conference on Digital Libraries …, 2019

… Keywords web archive, big data, distributed computation 1 Introduction Web preservation organizations such as Common Crawl or Internet Archive are common sources of web archive data … We use a data set from Common Crawl May 2018 collection …


Web Engineering: 19th International Conference, ICWE 2019, Daejeon, South Korea, June 11–14, 2019, Proceedings

Page 1. Maxim Bakaev Flavius Frasincar In-Young Ko (Eds.) Web Engineering 19th International Conference, ICWE 2019 Daejeon, South Korea, June 11–14, 2019 Proceedings 123 Page 2. Lecture Notes in Computer Science …


Web table integration and profiling for knowledge base augmentation

Page 1. Web Table Integration and Profiling for Knowledge Base Augmentation Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Universität Mannheim …


Web View: Measuring & Monitoring Representative Information on Websites

A Saverimoutou, B Mathieu, S Vaton - ICIN 2019-QOE-MANAGEMENT 2019, 2019

… XRay [8] and AdFisher run automated personalization detection experiments and Common Crawl 7 uses an Apache Nutch based crawler … 4http://phantomjs. org/ 5https://www.seleniumhq.org/ 6https://github.com/ghostwords/chameleon …


WebIsAGraph: A Very Large Hypernymy Graph from a Web Corpus

F Stefano, I Finocchi, SP Ponzetto, V Paola - Sixth Italian Conference on …, 2019

S Faralli, I Finocchi, SP Ponzetto, P Velardi - 2019

… Abstract In this paper, we present WebIsAGraph, a very large hypernymy graph compiled from a dataset of is-a relationships ex- tracted from the CommonCrawl … This is because, due to their large size, source input corpora …


What a neural language model tells us about spatial relations

M Ghanimifard, S Dobnik - Proceedings of the Combined Workshop on Spatial …, 2019

… Finally, we also use pre-trained GloVe embeddings on the Common Crawl (CC) dataset with 42B tokens4 … On multi-word test suite the P-vectors perform slightly better. On both test suites, GloVe trained on Common Crawl performs …


A Haller, JD Fernández, MR Kamdar, A Polleres - Working Papers on Information …, 2019

Page 1. What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web Armin Haller, Javier D. Fernández, Maulik R. Kamdar, Axel Polleres Arbeitspapiere zum Tätigkeitsfeld …


What does Neural Bring? Analysing Improvements in Morphosyntactic Annotation and Lemmatisation of Slovenian, Croatian and Serbian

N Ljubešić, K Dobrovoljc - Proceedings of the 7th Workshop on Balto-Slavic …, 2019

… neural morphosyntactic taggers, we also experiment with various embeddings, mostly (1) the original CoNLL 2017 word2vec (w2v) embeddings for Slovenian and Croatian (Ginter et al., 2017) (there are none available for …


Who Needs Words? Lexicon-Free Speech Recognition

T Likhomanenko, G Synnaeve, R Collobert - arXiv preprint arXiv:1904.04479, 2019

… char GCNN-20B no 6.4 2.7 3.6 1.5 4https://github.com/facebookresearch/wav2letter 5Speaker adaptation; pronunciation lexicon 612k hours AM train set and common crawl LM 7Speaker adaptation; 3k acoustic states 8Data augmentation; n-gram LM …


WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia

H Schwenk, V Chaudhary, S Sun, H Gong, F Guzmán - arXiv preprint arXiv …, 2019

… recall. In this work, we chose the global mining op- tion. This will allow us to scale the same ap- proach to other, potentially huge, corpora for which document-level alignments are not easily available, eg Common Crawl. An …


WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale

K Sakaguchi, RL Bras, C Bhagavatula, Y Choi - arXiv preprint arXiv:1907.10641, 2019

… Ensemble Neural LMs Trinh and Le (2018) is one of the first attempts to apply a neural language model which is pre-trained on a very large corpora (including LM-1-Billion, CommonCrawl, SQuAD, and Gutenberg Books). In …


Word Embedding Based Extension of Text Categorization Topic Taxonomies

T Eljasik-Swoboda, F Engel, M Kaufmann, M Hemmje

… ArgumenText is a practical implementation of an AM engine (Stab et al., 2018). It employs a two-step mechanism in which a large collection of documents (http://commoncrawl.org/, in Stab et al.'s experiment with 683 …


Page 1. MASTER'S THESIS Word Embedding Models for Query Expansion in Answer Passage Retrieval NIRMAL ROY Page 2. Page 3. Word Embedding Models for Query Expansion in Answer Passage Retrieval THESIS submitted …


Word Embedding Visualization Via Dictionary Learning

J Zhang, Y Chen, B Cheung, BA Olshausen - arXiv preprint arXiv:1910.03833, 2019

… similar. For simplicity, we show the results for the 300 dimensional GloVe word vectors[30] pretrained on CommonCrawl [2]. We shall discuss the difference across different embedding models at the end in this section. Once …


Word Embeddings (Also) Encode Human Personality Stereotypes

O Agarwal, F Durupınar, NI Badler, A Nenkova - … of the Eighth Joint Conference on …, 2019

… or profession. We experimented with GloVe representations (Pennington et al., 2014) trained on Common crawl (6B tokens, 400K vocab, 300d) and symmetric pattern (SP) based representations (Schwartz et al., 2015). We …


Page 1. UUDM Project Report 2019:15 Examensarbete i matematik, 30 hp Handledare: David Sumpter Examinator: Denis Gaidashev Maj 2019 Department of Mathematics Uppsala University Word Embeddings and Gender Stereotypes in Swedish and English …


Word Embeddings for Fine-Grained Sentiment Analysis

D Bacon, R Dalal, MRD Kodandarama, MR Hari…

… Lastly, we considered the word embedding sub-model. We used the GLoVe word vectoring [11] trained on Common Crawl [https://commoncrawl.org/] as implemented by spaCy [7]. This resulted in a vector-dimension of 300 for each word …


Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey

E Çano, M Morisio - arXiv preprint arXiv:1902.00753, 2019

… This bundle contains data of Common Crawl (http: //commoncrawl.org/), a nonprofit organization that builds and maintains free and public text sets by crawling the Web. CommonCrawl42 is a highly reduced version easier and faster to work with …


Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation

K Avetisyan, T Ghukasyan - arXiv preprint arXiv:1906.03134, 2019

… A year later, Facebook released another batch of fastText embeddings, trained on Common Crawl and Wikipedia [2]. Other publicly available embeddings include 4 … these embeddings were trained on Wikipedia and Common Crawl, using CBOW architecture with …


Word Embeddings in Low Resource Gujarati Language

I Joshi, P Koringa, S Mitra - 2019 International Conference on Document Analysis …, 2019

… (2014) released GloVe models trained on Wikipedia, Gigaword and Common Crawl (840B tokens). A notable effort is the work of Al-Rfou et al … Word embeddings for Gujarati language were released as a part of …


Word Similarity Datasets for Thai: Construction and Evaluation

P Netisopakul, G Wohlgenannt, A Pulich - arXiv preprint arXiv:1904.04307, 2019

… The models are trained on Common Crawl and Wikipedia corpora using fastText [13], regarding settings they report the us- age of the CBOW algorithm, 300 dimensions, a window size of 5 and 10 negatives. The model is large and contains 2M vectors …


Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes

AG Soler, M Apidianaki, A Allauzen - arXiv preprint arXiv:1905.08377, 2019

… al., 2014). We use 300-dimensional GloVe embeddings pre-trained on Common Crawl (840B tokens).5 The representation of a sentence is obtained by averaging the GloVe embeddings of the words in the sentence. SIF (Smooth …


Word-embedding data as an alternative to questionnaires for measuring the affective meaning of concepts

… Here we include information from both algorithms. The GloVe embeddings we use have been trained on text obtained from Wikipedia, Twitter, and Common Crawl. The Word2vec embeddings we use are trained on the Google News Corpus …


Word-Embeddings and Grammar Features to Detect Language Disorders in Alzheimer's Disease Patients

JS Guerrero-Cristancho, JC Vásquez-Correa… - TecnoLógicas, 2020

… occurrence in a document [13]. Said authors considered a pre-trained model with the Common Crawl dataset, whose vocabulary size exceeds the 2 million and contains 840 billion words. A logistic regression classifier and …


Z Wu, Y Song, S Huang, Y Tian, F Xia - Proceedings of the 18th BioNLP Workshop …, 2019

Page 1. Proceedings of the BioNLP 2019 workshop, pages 415–426 Florence, Italy, August 1, 2019. c 2019 Association for Computational Linguistics 415 WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language Inference …


X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension

M Abdou, C Sas, R Aralikatte, I Augenstein, A Søgaard - arXiv preprint arXiv …, 2019

… All monolingual models' word embeddings were initialised using fastText embeddings trained on each language's Wikipedia and common crawl corpora,7 except for the comparison experiments described in sub-section …


Z Yang, Z Dai, Y Yang, J Carbonell, R Salakhutdinov… - arXiv preprint arXiv …, 2019

Page 1. XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang∗1, Zihang Dai∗12, Yiming Yang1, Jaime Carbonell1, Ruslan Salakhutdinov1, Quoc V. Le2 1Carnegie Mellon University, 2Google …


YNU Wb at HASOC 2019: Ordered Neurons LSTM with Attention for Identifying Hate Speech and Offensive Language

B Wang, SL Yunxia Ding, X Zhou - Proceedings of the 11th annual meeting of the …, 2019

… And the pre-training word vector we used is fastText, which is provided by Mikolov et al. [7]. It is a 2 million word vector trained using subword information on Common Crawl with 600B tokens, and its dimension is 300. 4.3 Result …


YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language

B Wang, X Zhou, X Zhang - Proceedings of the 13th International Workshop on …, 2019

… FastText is provided by Mikolov et al. (Mikolov et al., 2018), it is a 2 million word vector trained using subword information on Common Crawl with 600B tokens, and its dimension is 300. Glove is provided by Jeffrey Pennington et al …


Zastosowania metody rzutu przypadkowego w głębokich sieciach neuronowych

Page 1. Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie Wydział Informatyki, Elektroniki i Telekomunikacji Katedra Informatyki Rozprawa doktorska Zastosowania metody rzutu przypadkowego w głębokich …


Zero-Resource Cross-Lingual Named Entity Recognition

MS Bari, S Joty, P Jwalapuram - arXiv preprint arXiv:1911.09812, 2019

… We use FastText embeddings (Grave et al. 2018), which are trained on Common Crawl and Wikipedia, and SGD with a gradient clipping of 5.0 to train the model. We found that the learning rate was crucial for training, and …


Zero-Resource Neural Machine Translation with Monolingual Pivot Data

… We use all available parallel corpora for EN↔DE (Europarl v7, Common Crawl, and News Commentary v11) and for EN↔RU (Common Crawl, News Commentary v11, Yandex Corpus, and Wiki Headlines) to train the initial …


Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging

J Choi, J Lee, J Park, J Nam - arXiv preprint arXiv:1906.08615, 2019

… We utilized a pretrained GloVe model available online. It contains 19 million vocabularies with 300 dimensional embedding trained from documents in Common Crawl data. We then evaluated the model on MTAT and GTZAN …


Zero-Shot Question Classification Using Synthetic Samples

H Fu, C Yuan, X Wang, Z Sang, S Hu, Y Shi - 2018 5th IEEE International Conference …, 2019

… The detailed data set is listed in Table 1. All experiments follow the principle of counterpart parameters. The Chinese and English word vectors are pre-trained using Glove respectively on Samsung and Common Crawl corpus. The word dimension is 300 …


Zero-Shot Semantic Segmentation via Variational Mapping

N Kato, T Yamasaki, K Aizawa - Proceedings of the IEEE International Conference on …, 2019

… Dataset Unseen classes PASCAL-50 aeroplane, bicycle, bird, boat, bottle PASCAL-51 bus, car, cat, chair, cow PASCAL-52 diningtable, dog, horse, motorbike, person PASCAL-53 potted plant, sheep, sofa, train, tv/monitor …