PPT-Introduction to Deep Processing Techniques for NLP

Author : stefany-barnette | Published Date : 2017-05-15

Deep Processing Techniques for NLP Ling 571 January 5 2015 GinaAnne Levow Roadmap Motivation Applications Language and Thought Knowledge of Language Crosscutting

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Introduction to Deep Processing Techniques for NLP: Transcript

Deep Processing Techniques for NLP Ling 571 January 5 2015 GinaAnne Levow Roadmap Motivation Applications Language and Thought Knowledge of Language Crosscutting themes Ambiguity Evaluation amp Multi. 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 . Semantic Role Labeling. Syntactic Variation. Last week, Min broke the window with a hammer.. The window was broken with a hammer by Min last week. With a hammer, Min broke the window last week. Last week, the window was broken by Min with a hammer. Regina Barzilay. What is NLP?. Goal: intelligent processing of human language. Not just effective string matching. Applications of NLP technology:. Less ambitious (but practical goals): spelling corrections, name entity extraction. Properties of Propositional Logic. Pros. Compositional. Declarative. Cons. Limited expressive power. Represents facts. First Order Logic. Used to represent. Objects – Martin the cat. Relations – Martin and Moses are brothers. New-Generation Models & Methodology for Advancing . AI & SIP. Li Deng . Microsoft Research, Redmond, . USA. Tianjin University, July 2-5, 2013. (including joint work with colleagues at MSR, U of Toronto, etc.) . 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 . Categorial. Grammar (CCG). Combinatory Categorial Grammar (CCG). Complex types. E.g., . X/Y. and . X\Y. These take an argument of type . Y. and return an object of type . X. . . X/Y – means that Y should appear on the right. 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. -. Kasami. -Younger (CKY) Parsing. Notes on Left Recursion. Problematic for many parsing methods. Infinite loops when expanding. But appropriate linguistically. NP -> DT N. NP -> PN. DT -> NP ‘s. 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. . SYFTET. Göteborgs universitet ska skapa en modern, lättanvänd och . effektiv webbmiljö med fokus på användarnas förväntningar.. 1. ETT UNIVERSITET – EN GEMENSAM WEBB. Innehåll som är intressant för de prioriterade målgrupperna samlas på ett ställe till exempel:. 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. 39OriginalNortheast IndiaPB Lalthanpuii1 B Lalruatfela2 Zoramdinthara3and H Lalthanzara11Department of Zoology 3Department of MizoPachhunga University College Aizawl 796001 India2Department of Zoology by Hua Xu. Recent Activities. ETL tool development. Note Type Normalization. COVID-19 lab test normalization . A Potential ETL Workflow for NLP. Note. Note_NLP. Measure-. ment. Condition. Procedure. Drug.

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