PPT-NLP Text similarity Introduction

Text Similarity Motivation People can express the same concept or related concepts in many different ways For example the plane leaves at 12pm vs the flight departs at noon Text similarity is a key component of Natural Language Processing. Christopher Manning. Stanford University. Digital Humanities 2011. http://nlp.stanford.edu/~manning/courses/DigitalHumanities. /. . Commencement 2010. My humanities qualifications. B.A. (. Hons. ), Australian National University. . Multi-label Protein Subcellular Localization. Shibiao WAN and Man-Wai MAK. The Hong Kong Polytechnic University. Sun-Yuan KUNG. Princeton University. Outline. Introduction and Motivation. Retrieval of GO Terms. -. based Clustering. Mohammad. . Rezaei. , Pasi Fränti. rezaei@cs.uef.fi. Speech. and . Image. . Processing. . Unit. University of Eastern Finland. . August 2014. Keyword-Based Clustering. An object such as a text document, website, movie and service can be described by a set of keywords. WordNet. Lubomir. . Stanchev. Example . Similarity Graph. Dog. Cat. 0.3. 0.3. Animal. 0.8. 0.2. 0.8. 0.2. Applications. If we type . automobile. . in our favorite Internet search engine, for example Google or Bing, then all top results will contain the word . these theories have explanatory power domains partially role of relational judgments. Previous structural and aspects of notion of relational similarity by the fact that and her some ways there is in Morphology and the Lexicon. Mental Lexicon. What is the meaning of cat? Its pronunciation? Part of speech?. What is the meaning of . wug. ?. What is the meaning of . cluvious. ?. Compare . traftful. and . a Multi-Layered Indexing Approach. Yongjiang Liang, . Peixiang Zhao. CS @ FSU. zhao@cs.fsu.edu. Outline. Introduction. State-of-the-art solutions. ML-Index & similarity search. Experiments. Conclusion. Language Annotation, Modeling, and Processing . Toolkit (CLAMP) . Hua Xu. School of Biomedical Informatics, . University . of Texas Health Science Center at Houston . 1. The Transportability Problem of . HEADLINE. Body. text,. body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text. Who wrote which Federalist papers?. 1787-8: anonymous essays try to convince New York to ratify U.S Constitution: . . Jay, Madison, Hamilton. . Authorship of 12 of the letters in dispute. 1963: solved by . Jimmy Lin. The . iSchool. University of Maryland. Wednesday, September 2, 2009. NLP. IR. About Me. Teaching Assistant: . Melissa Egan. CLIP. About You (pre-requisites). Must be interested in NLP. Must have strong computational background. Edit Distance. Spelling Similarity. Typos:. Brittany Spears -> Britney Spears. Catherine Hepburn -> Katharine Hepburn. Reciept. -> receipt. Variants in spelling:. Theater -> theatre. Who is this?. Jiho . Han. Ronny (. Dowon. ) . Ko. Objective:. automatically generate the summary of review extracting the strength/weakness of the product. Use NLP techniques to predict ratings. Similar to sentimental analysis. Dan Jurafsky. Stanford University. Spring 2020 . Introduction and Course Overview. Thanks to . Tsvetkov. and Black course . for ideas and slides!. How should we use NLP for good and not for bad?. The common misconception is that language has to do with .