Cross Curriculum Lesson with the Aid of Google's Ngram
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Corpora: Google Ngram Viewer and the Corpus of Historical American English
EuroAmerican Journal of Applied Linguistics and Languages E JournALL Volume 1, Issue 1, November 2014, pages 48 68 ISSN 2376 905X DOI - - www.e journall.org- http://dx.doi.org/10.21283/2376905X.1.4 - Exploring mega-corpora: Google Ngram Viewer and the Corpus of Historical American English ERIC FRIGINALa1, MARSHA WALKERb, JANET BETH RANDALLc aDepartment of Applied Linguistics and ESL, Georgia State University bLanguage Institute, Georgia Institute of Technology cAmerican Language Institute, New York University, Tokyo Received 10 December 2013; received in revised form 17 May 2014; accepted 8 August 2014 ABSTRACT EN The creation of internet-based mega-corpora such as the Corpus of Contemporary American English (COCA), the Corpus of Historical American English (COHA) (Davies, 2011a) and the Google Ngram Viewer (Cohen, 2010) signals a new phase in corpus-based research that provides both novice and expert researchers immediate access to a variety of online texts and time-coded data. This paper explores the applications of these corpora in the analysis of academic word lists, in particular, Coxhead’s (2000) Academic Word List (AWL). Coxhead (2011) has called for further research on the AWL with larger corpora, noting that learners’ use of academic vocabulary needs to address for the AWL to be useful in various contexts. Results show that words on the AWL are declining in overall frequency from 1990 to the present. Implications about the AWL and future directions in corpus-based research utilizing mega-corpora are discussed. Keywords: GOOGLE N-GRAM VIEWER, CORPUS OF HISTORICAL AMERICAN ENGLISH, MEGA-CORPORA, TREND STUDIES. ES La creación de megacorpus basados en Internet, tales como el Corpus of Contemporary American English (COCA), el Corpus of Historical American English (COHA) (Davies, 2011a) y el Visor de Ngramas de Google (Cohen, 2010), anuncian una nueva fase en la investigación basada en corpus, pues proporcionan, tanto a investigadores noveles como a expertos, un acceso inmediato a una gran diversidad de textos online y datos codificados con time-code. -
BEYOND JEWISH IDENTITY Rethinking Concepts and Imagining Alternatives
This book is subject to a CC-BY-NC license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/ BEYOND JEWISH IDENTITY Rethinking Concepts and Imagining Alternatives This book is subject to a CC-BY-NC license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/ This book is subject to a CC-BY-NC license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/ BEYOND JEWISH IDENTITY rethinking concepts and imagining alternatives Edited by JON A. LEVISOHN and ARI Y. KELMAN BOSTON 2019 This book is subject to a CC-BY-NC license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/ Library of Congress Control Number:2019943604 The research for this book and its publication were made possible by the generous support of the Jack, Joseph and Morton Mandel Center for Studies in Jewish Education, a partnership between Brandeis University and the Jack, Joseph and Morton Mandel Foundation of Cleveland, Ohio. © Academic Studies Press, 2019 ISBN 978-1-644691-16-8 (Hardcover) ISBN 978-1-644691-29-8 (Paperback) ISBN 978-1-644691-17-5 (Open Access PDF) Book design by Kryon Publishing Services (P) Ltd. www.kryonpublishing.com Cover design by Ivan Grave Published by Academic Studies Press 1577 Beacon Street Brookline, MA 02446, USA [email protected] www.academicstudiespress.com Effective May 26th 2020, this book is subject to a CC-BY-NC license. To view a copy of this license, visit https://creativecommons.org/licenses/ by-nc/4.0/. -
CS15-319 / 15-619 Cloud Computing
CS15-319 / 15-619 Cloud Computing Recitation 13 th th November 18 and 20 , 2014 Announcements • Encounter a general bug: – Post on Piazza • Encounter a grading bug: – Post Privately on Piazza • Don’t ask if my answer is correct • Don’t post code on Piazza • Search before posting • Post feedback on OLI Last Week’s Project Reflection • Provision your own Hadoop cluster • Write a MapReduce program to construct inverted lists for the Project Gutenberg data • Run your code from the master instance • Piazza Highlights – Different versions of Hadoop API: Both old and new should be fine as long as your program is consistent Module to Read • UNIT 5: Distributed Programming and Analytics Engines for the Cloud – Module 16: Introduction to Distributed Programming for the Cloud – Module 17: Distributed Analytics Engines for the Cloud: MapReduce – Module 18: Distributed Analytics Engines for the Cloud: Pregel – Module 19: Distributed Analytics Engines for the Cloud: GraphLab Project 4 • MapReduce – Hadoop MapReduce • Input Text Predictor: NGram Generation – NGram Generation • Input Text Predictor: Language Model and User Interface – Language Model Generation Input Text Predictor • Suggest words based on letters already typed n-gram • An n-gram is a phrase with n contiguous words Google-Ngram Viewer • The result seems logical: the singular “is” becomes the dominant verb after the American Civil War. Google-Ngram Viewer • “one nation under God” and “one nation indivisible.” • “under God” was signed into law by President Eisenhower in 1954. How to Construct an Input Text Predictor? 1. Given a language corpus – Project Gutenberg (2.5 GB) – English Language Wikipedia Articles (30 GB) 2. -
Internet and Data
Internet and Data Internet and Data Resources and Risks and Power Kenneth W. Regan CSE199, Fall 2017 Internet and Data Outline Week 1 of 2: Data and the Internet What is data exactly? How much is there? How is it growing? Where data resides|in reality and virtuality. The Cloud. The Farm. How data may be accessed. Importance of structure and markup. Structures that help algorithms \crunch" data. Formats and protocols for enabling access to data. Protocols for controlling access and changes to data. SQL: Select. Insert. Update. Delete. Create. Drop. Dangers to privacy. Dangers of crime. (Dis-)Advantages of online data. [Week 1 Activity: Trying some SQL queries.] Internet and Data What Exactly Is \Data"? Several different aspects and definitions: 1 The entire track record of (your) online activity. Note that any \real data" put online was part of online usage. Exception could be burning CD/DVDs and other hard media onto a server, but nowadays dwarfed by uploads. So this is the most inclusive and expansive definition. Certainly what your carrier means by \data"|if you re-upload a file, it counts twice. 2 Structured information for a particular context or purpose. What most people mean by \data." Data repositories often specify the context and form. Structure embodied in formats and access protocols. 3 In-between is what's commonly called \Unstructured Information" Puts the M in Data Mining. Hottest focus of consent, rights, and privacy issues. Internet and Data How Much Data Is There? That is, How Big Is the Internet? Searchable Web Deep Web (I maintain several gigabytes of deep-web textual data. -
Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom
Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Durand, Neva C., James T. Robinson, Muhammad S. Shamim, Ido Machol, Jill P. Mesirov, Eric S. Lander, and Erez Lieberman Aiden. “Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom.” Cell Systems 3, no. 1 (July 2016): 99-101. As Published http://dx.doi.org/10.1016/j.cels.2015.07.012 Publisher Elsevier Version Final published version Citable link http://hdl.handle.net/1721.1/105759 Terms of Use Creative Commons Attribution 4.0 International License Detailed Terms http://creativecommons.org/licenses/by/4.0/ Tool Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom Graphical Abstract Authors Neva C. Durand, James T. Robinson, Muhammad S. Shamim, Ido Machol, Jill P. Mesirov, Eric S. Lander, Erez Lieberman Aiden Correspondence [email protected] In Brief We introduce Juicebox, a tool for exploring contact maps generated using Hi-C and other 3D genome-sequencing technologies. Users can zoom in and out interactively, just as a user of Google Earth might zoom in and out of a geographic map. Highlights d Juicebox enables users to explore Hi-C contact maps d Users can create maps from their own experimental data d Users can zoom in and out of a contact map in real time d Maps can be compared to 1D tracks, 2D feature sets, or one another Durand et al., 2016, Cell Systems 3, 99–101 July 27, 2016 ª 2016 Elsevier Inc. -
Introduction to Text Analysis: a Coursebook
Table of Contents 1. Preface 1.1 2. Acknowledgements 1.2 3. Introduction 1.3 1. For Instructors 1.3.1 2. For Students 1.3.2 3. Schedule 1.3.3 4. Issues in Digital Text Analysis 1.4 1. Why Read with a Computer? 1.4.1 2. Google NGram Viewer 1.4.2 3. Exercises 1.4.3 5. Close Reading 1.5 1. Close Reading and Sources 1.5.1 2. Prism Part One 1.5.2 3. Exercises 1.5.3 6. Crowdsourcing 1.6 1. Crowdsourcing 1.6.1 2. Prism Part Two 1.6.2 3. Exercises 1.6.3 7. Digital Archives 1.7 1. Text Encoding Initiative 1.7.1 2. NINES and Digital Archives 1.7.2 3. Exercises 1.7.3 8. Data Cleaning 1.8 1. Problems with Data 1.8.1 2. Zotero 1.8.2 3. Exercises 1.8.3 9. Cyborg Readers 1.9 1. How Computers Read Texts 1.9.1 2. Voyant Part One 1.9.2 3. Exercises 1.9.3 10. Reading at Scale 1.10 1. Distant Reading 1.10.1 2. Voyant Part Two 1.10.2 3. Exercises 1.10.3 11. Topic Modeling 1.11 1. Bags of Words 1.11.1 2. Topic Modeling Case Study 1.11.2 3. Exercises 1.11.3 12. Classifiers 1.12 1. Supervised Classifiers 1.12.1 2. Classifying Texts 1.12.2 3. Exercises 1.12.3 13. Sentiment Analysis 1.13 1. Sentiment Analysis 1.13.1 2. -
Google Ngram Viewer Turns Snippets Into Insight Computers Have
PART I Shredding the Great Books - or - Google Ngram Viewer Turns Snippets into Insight Computers have the ability to store enormous amounts of information. But while it may seem good to have as big a pile of information as possible, as the pile gets bigger, it becomes increasingly difficult to find any particular item. In the old days, helping people find information was the job of phone books, indexes in books, catalogs, card catalogs, and especially librarians. Goals for this Lecture 1. Investigate the history of digitizing text; 2. Understand the goal of Google Books; 3. Describe logistical, legal, and software problems of Google Books; 4. To see some of the problems that arise when old texts are used. Computers Are Reshaping Our World This class looks at ways in which computers have begun to change the way we live. Many recent discoveries and inventions can be attributed to the power of computer hardware (the machines), the development of computer programs (the instructions we give the machines), and more importantly to the ability to think about problems in new ways that make it possible to solve them with computers, something we call computational thinking. Issues in Computational Thinking What problems can computers help us with? What is different about how a computer seeks a solution? Why are computer solutions often not quite the same as what a human would have found? How do computer programmers write out instructions that tell a computer how to solve a problem, what problem to solve, and how to report the answer? How does a computer \think"? How does it receive instructions, store infor- mation in a memory, represent and manipulate the numbers and words and pictures and ideas that we refer to as we think about a problem? Computers are Part of a Complicated World We will see that making a computer carry out a task in a few seconds actually can take years of thinking, research, and experiment. -
Apache Hadoop & Spark – What Is It ?
Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark Apache Hadoop & Spark { What is it ? Demo Joseph Allemandou JoalTech 17 / 05 / 2018 1 / 23 Hello! Hadoop { Spark Overview Joseph Allemandou J. Allemandou Generalities Hadoop Spark Demo 2 / 23 Plan Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark 1 Generalities on High Performance Computing (HPC) Demo 2 Apache Hadoop and Spark { A Glimpse 3 Demonstration 3 / 23 More computation power: Scale up vs. scale out Hadoop { Spark Overview J. Allemandou Scale Up Scale out Generalities Hadoop Spark Demo 4 / 23 More computation power: Scale up vs. scale out Hadoop { Spark Overview Scale out J. Allemandou Scale Up Generalities Hadoop Spark Demo 4 / 23 Parallel computing Hadoop { Spark Overview Things to consider when doing parallel computing: J. Allemandou Partitioning (tasks, data) Generalities Hadoop Spark Communications Demo Synchronization Data dependencies Load balancing Granularity IO Livermore Computing Center - Tutorial 5 / 23 Looking back - Since 1950 Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark Demo Figure: Google Ngram Viewer 6 / 23 Looking back - Since 1950 Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark Demo Figure: Google Ngram Viewer 6 / 23 Looking back - Since 1950 Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark Demo Figure: Google Ngram Viewer 6 / 23 Looking back - Recent times Hadoop { Spark Overview J. Allemandou Generalities Hadoop Spark Demo Figure: Google Trends 7 / 23 Same problem, different tools Hadoop { Spark Overview J. Allemandou Generalities Supercomputer Big Data Hadoop Spark Demo Dedicated hardware Commodity hardware Message Passing Interface 8 / 23 MPI Hadoop { Spark Overview J. Allemandou Generalities C / C++ / Fortran / Python Hadoop Spark Demo Low-level API - Send / receive messages a lot to do manually split the data assign tasks to workers handle synchronisation handle errors 9 / 23 Hadoop + Spark Hadoop { Spark Overview J. -
Improved Aedes Aegypti Mosquito Reference Genome Assembly Enables Biological Discovery and Vector Control
bioRxiv preprint doi: https://doi.org/10.1101/240747; this version posted December 29, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Improved Aedes aegypti mosquito reference genome assembly enables biological discovery and vector control Benjamin J. Matthews1-3*, Olga Dudchenko4-7*, Sarah Kingan8*, Sergey Koren9, Igor Antoshechkin10, Jacob E. Crawford11, William J. Glassford12, Margaret Herre1,3, Seth N. Redmond13,14, Noah H. Rose15, Gareth D. Weedall16,17, Yang Wu18,19, Sanjit S. Batra4-6, Carlos A. Brito-Sierra20,21, Steven D. Buckingham22, Corey L Campbell23, Saki Chan24, Eric Cox25, Benjamin R. Evans26, Thanyalak Fansiri27, Igor Filipović28, Albin Fontaine29-32, Andrea Gloria-Soria26, Richard Hall8, Vinita S. Joardar25, Andrew K. Jones33, Raissa G.G. Kay34, Vamsi K. Kodali25, Joyce Lee24, Gareth J. Lycett16, Sara N. Mitchell11, Jill Muehling8, Michael R. Murphy25, Arina D. Omer4-6, Frederick A. Partridge22, Paul Peluso8, Aviva Presser Aiden4,5,35,36, Vidya Ramasamy33, Gordana Rašić28, Sourav Roy37, Karla Saavedra-Rodriguez23, Shruti Sharan20,21, Atashi Sharma38, Melissa Laird Smith8, Joe Turner39, Allison M. Weakley11, Zhilei Zhao15, Omar S. Akbari40, William C. Black IV23, Han Cao24, Alistair C. Darby39, Catherine Hill20,21, J. Spencer Johnston41, Terence D. Murphy25, Alexander S. Raikhel37, David B. Sattelle22, Igor V. Sharakhov38,42, Bradley J. White11, Li Zhao43, Erez Lieberman Aiden4-7,13, Richard S. Mann12, Louis Lambrechts29,31, Jeffrey R. Powell26, Maria V. Sharakhova38,42, Zhijian Tu19, Hugh M. -
Conceptboard Совместное Редактирование, Виртуальная Д
1. Виртуальные доски: Conceptboard совместное редактирование, виртуальная доска DabbleBoard совместное редактирование без регистрации Educreations виртуальная доска, классы, категории, мультимедиа (онлайн и как приложение к iPad) FlockDraw - cовместное рисование и работа с виртуальной доской Notaland виртуальная доска для групповой работы - интеграция различного контента Primary Paint виртуальная доска для совместной работы без регистрации Popplet - виртуальная стена (доска) для работы с мультимедиа объектами в группе RealtimeBoard виртуальные доски для проектов на русском языке Rizzoma - виртуальная площадка для коллективной работы Scriblink виртуальная доска Scrumlr виртуальная доска со стикерами. Групповая работа Twiddla виртуальная интерактивная доска Vyew сервис совещаний, обучения, виртуальная доска Writeboard совместное редактирование WikiWall работа в группе с информацией 2. Графика онлайн (редакторы, хостинг, анимация, коллажи): artPad -онлайн рисовалка Aviary фоторедактор редактируем фото Aviary Phoenix Совместное редактирование рисунков BannerSnack создание банеров Befunky -редактируем фото, создаем коллаж Blingee создание анимированных изображений Caption.iT создание коллажей с использованием множества шаблонов Clay Yourself создание аватарок ( портретов) из наборов графических примитивов CreateCollage - сервис русский для быстрого создания коллажей из 2-6 фотографий. Doink -мультипликация Dermandar - фотопанорамы DisaPainted создание анимации в сети Drav.to - рисование онлайн Draw a Shtickman анимация, рисуем на сервисе Drawball -
Tracing Significant Change in 17Th-Century English Lexis: the Civil-War Effect
TRACING SIGNIFICANT CHANGE IN 17TH-CENTURY ENGLISH LEXIS: THE CIVIL-WAR EFFECT Table 1. Number of words whose frequencies are significantly different in the two periods of the CEEC (1600–1639 and 1640–1681), at various significance thresholds α (n = 46,440). α Log-likelihood ratio test Bootstrap test Both 0.01 2,685 (6 %) 2,365 (5 %) 2,199 (5 %) 0.001 1,400 (3 %) 1,209 (3 %) 1,108 (2 %) 0.0001 937 (2 %) 759 (2 %) 722 (2 %) For more information, see Lijffijt et al. (forthcoming 2012). REFERENCES CEEC = Corpus of Early English Correspondence. 1998. Compiled by Terttu Nevalainen, Helena Raumolin-Brunberg, Jukka Keränen, Minna Nevala, Arja Nurmi & Minna Palander-Collin at the Department of English, University of Helsinki. http://www.helsinki.fi/varieng/CoRD/corpora/CEEC/ Dunning, Ted. 1993. “Accurate methods for the statistics of surprise and coincidence”. Computational Linguistics 19(1): 61–74. Google Books Ngram Viewer. http://books.google.com/ngrams/ HT = Historical Thesaurus of the Oxford English Dictionary. 2009. Edited by Christian Kay, Jane Roberts, Michael Samuels & Irené Wotherspoon. OED Online. http://www.oed.com/thesaurus Kilgarriff, Adam. 2001. “Comparing corpora”. International Journal of Corpus Linguistics 6(1): 97–133. Lijffijt, Jefrey, Tanja Säily & Terttu Nevalainen. Forthcoming 2012. “CEECing the baseline: Lexical stability and significant change in a historical corpus”. To appear in the proceedings of the Helsinki Corpus Festival. http://www.helsinki.fi/varieng/journal/ Lijffijt, Jefrey, Terttu Nevalainen, Tanja Säily, Panagiotis Papapetrou, Kai Puolamäki & Heikki Mannila. Forthcoming. “Significance testing of word frequencies in corpora”. Submitted to International Journal of Corpus Linguistics. Michel, Jean-Baptiste, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K. -
Google Ngram Viewer by Andrew Weiss
Google Ngram Viewer By Andrew Weiss Digital Services Librarian California State University, Northridge Introduction: Google, mass digitization and the emerging science of culturonomics Google Books famously launched in 2004 with great fanfare and controversy. Two stated original goals for this ambitious digitization project were to replace the generic library card catalog with their new “virtual” one and to scan all the books that have ever been published, which by a Google employee’s reckoning is approximately 129 million books. (Google 2014) (Jackson 2010) Now ten years in, the Google Books mass-digitization project as of May 2014 has claimed to have scanned over 30 million books, a little less than 24% of their overt goal. Considering the enormity of their vision for creating this new type of massive digital library their progress has been astounding. However, controversies have also dominated the headlines. At the time of the Google announcement in 2004 Jean Noel Jeanneney, head of Bibliothèque nationale de France at the time, famously called out Google’s strategy as excessively Anglo-American and dangerously corporate-centric. (Jeanneney 2007) Entrusting a corporation to the digitization and preservation of a diverse world-wide corpus of books, Jeanneney argues, is a dangerous game, especially when ascribing a bottom-line economic equivalent figure to cultural works of inestimable personal, national and international value. Over the ten years since his objections were raised, many of his comments remain prescient and relevant to the problems and issues the project currently faces. Google Books still faces controversies related to copyright, as seen in the current appeal of the Author’s Guild v.