PPT-CS 124/LINGUIST 180 From Languages to Information

Dan Jurafsky Stanford University Social Networks Small Worlds Weak Ties and Power Laws Slides from Jure Leskovec Lada Adamic James Moody Bing Liu Networks I nformation in networks not just text. References http://bjp.rcpsych.org/content/180/2/174#BIBL permissionsReprints/ permissions@rcpsych.ac.ukwrite to to this article atYou can respond /letters/submit/bjprcpsych;180/2/174 from Downloaded x-raster()ကxclass:RasterLayerdimensions:180,360,64800(nrow,ncol,ncell)resolution:1,1(x,y)extent:-180,180,-90,90(xmin,xmax,ymin,ymax)coord.ref.:+proj=longlat+datum=WGS84+ellps=WGS84+towgs84=0,0 Eric Brenner. Paul Carpenter. Daniel Ehrenberg. Aaron McCarty. Travis Raines. Advised by Jeff . Ondich. Defining the Problem. What is optical character recognition (OCR)?. Input: an image of some text. b(.+!(&0!.-2!&-,1%.0)4!($$)%0*!%.!'-#$(&(1%30!$+4'8-)-:46!Y-&!0E(#$)09!0E$0&%#0.1()!(++%+1(.1+!(&0!-/10.!50$1!D)%.*!(D-,1!'&,'%()!(+$0'1+!-/!180!0E$0&%#0.1!1-!$&030.1!180#!/&-#!%.(*30&10.1)4!+%:.())%. From Languages . to Information. Conversational Agents. Dan Jurafsky. Stanford University. Conversational Agents . AKA Dialog Agents. Phone-based Personal Assistants . . SIRI, Cortana, Google Now. From Languages . to Information. Conversational Agents. Dan Jurafsky. Stanford University. Conversational Agents . AKA Dialog Agents. Phone-based Personal Assistants . . SIRI, Cortana, Google Now. LCD Text Display. Keypads and Time Slicing. Interrupts. adapted from . T. Murphy’s . lectures. 2×16 LCD . Typically 5×8 dots per character. Note 16 pins: indicator of common interface. Phys 124: Lecture 4. Adapted from T. Murphy’s lectures. The Rubric, Once Again. Sense some real-world quantity. input: analog or digital. sensor or user input (switches, keypad). Process the information. code in software. Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Unix for Poets . Dan Jurafsky. (original by Ken Church, modifications by me and Chris Manning). Stanford University . Unix for Poets. Text is everywhere. The Web. Dictionaries, corpora, email, etc. . +?!/%!)(*'4?/'&./&'+-!6%??+?!/%!/'4,)/)%(46!J(%76+,0+!4(,!)(/4(0)86+!.&6/&'46!5+')/40+-!4(,!'+9+'?46!%*!5+46/5!4(,!,+9+6%21+(/!04)(?!14,+-!7)/5!)124./!%(!*&/&'+!0+(+'4/)%(?A!#:$!7'83#9%/"(/54/! 0%9+'( 286Hong Kong 27 1530 3348 89101 106118 124137 179193 197211 276 278 281Human rights 1 6 137 161174 241243 247 265IIdentities 3 33 52 93 106 124 143 162 198 236 256 276Immigrants 3 6 35 98 106 126 161 Provide second grade teachers and parents with 180 daily practice activities to build and gauge students\' reading comprehension and word study skills, writing proficiency, and mathematical fluency. Great for after school programs, intervention programs, or even as a workbook used at home, students will gain regular practice through these quick, yet rigorous activities. Choose from a variety of fiction and nonfiction passages included in 180 Days of Reading, theme-based units that help guide students through the five steps of the writing process with 180 Days of Writing, mathematics activities tied to specific mathematical concepts in 180 Days of mathematics, and much more!