PPT-Introduction to NLP CMSC 723: Computational Linguistics I ― Session #1

Jimmy Lin The iSchool University of Maryland Wednesday September 2 2009 NLP IR About Me Teaching Assistant Melissa Egan CLIP About You prerequisites Must be interested in NLP Must have strong computational background. 2012 Association for Computational Linguistics You Had Me at Hello How Phrasing Affects Memorability Cristian DanescuNiculescuMizil Justin Cheng Jon Kleinberg Lillian Lee Department of Computer Science Cornell University cristiancscornelledu jc882co 2014 Association for Computational Linguistics Fast and Robust Neural Network Joint Models for Statistical Machine Translation Jacob Devlin Rabih Zbib Zhongqiang Huang Thomas Lamar Richard Schwartz and John Makhoul Raytheon BBN Technologies 10 Moult guse Abstract This paper deals with the problem of recognizing and extracting acronym de64257nition pairs in Swedish medical texts This project applies a rulebased method to solve the acronym recognition task and compares and evaluates the results of System fault A characteristic of a software system that can lead to a system error For example failure to initialize a variable could lead to that variable having the wrong value when it is used Human error or mistake Human behavior that results in Functional Programming with OCaml. CMSC 330. 2. Review. Recursion is how all looping is done. OCaml can easily pass and return functions. CMSC 330. 3. The Call Stack in C/Java/etc.. void f(void) {. int x;. Context-Free . Grammars. Ambiguity . CMSC 330. 2. Review. Why should we study CFGs?. What are the four parts of a CFG?. How do we tell if a string is accepted by a CFG?. What. ’. s a parse tree?. CMSC 330.
        
               
       Longman Lancaster corpus: 30 million words. ____________________________ Reference corpora have a fixed size (e.g., the British National Corpus Monitor corpora are expandable (e.g., the Bank of Engli Jimmy Lin. The . iSchool. University of Maryland. Wednesday, September 23, 2009. Source: Calvin and Hobbs. Today’s Agenda. What are parts of speech (POS)?. What is POS tagging?. Methods for automatic POS tagging. Jimmy Lin. The . iSchool. University of Maryland. Wednesday, September 30, 2009. Today’s Agenda. The great leap forward in NLP. Hidden Markov models (HMMs). Forward algorithm. Viterbi. . decoding. Fakry. . Hamdani. LINGUISTICS. Linguistics . (. n.. ) The scientific study of language; also called . linguistic . science. . (. David Crystal:2008). Linguistics. is a comparatively new science, or new, at least, in the form it has taken in recent years. The science seeks to answer the following questions: (a) what exactly do we know when we know a language (b) how is this knowledge acquired and (c) how is such knowledge used? (Petra). The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand