PPT-NLP Introduction to

Author : alida-meadow | Published Date : 2017-04-26

Natural Language Processing Introduction Language and Communication Speaker Intention goals shared knowledge and beliefs Generation tactical Synthesis text or speech

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Natural Language Processing Introduction Language and Communication Speaker Intention goals shared knowledge and beliefs Generation tactical Synthesis text or speech Listener Perception. By Cindy Carless. 14 Nov 14. What a mouthful…. So much in fact that I thought I had bitten off more than I could chew…. Yet for “Tasting” . LetsTest. it seems very appropriate. Some appetisers to focus on. Detecting Questions in Micro-text. Kyle Dent <. kdent@parc.com. >. Original Question: Do people use Twitter to ask questions?. First Answer: Of course.. But to what extent and what kinds of questions?. 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. Subproblems. . Meliha. . Yetisgen-Yildiz. From last week’s discussion. Presentation. Schedule. : . http. ://faculty.washington.edu/melihay/. MEBI591C.htm. 50 . minutes . presentation+discussion+question. 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 . Introduction. Polysemy. Words have multiple senses. Example. Let’s have a drink in the bar. I have to study for the bar. Bring me a chocolate bar. Homonymy. May I come in?. Let’s meet again in May. 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 . S . -> NP VP. NP -> DT N | NP PP. PP -> PRP NP. VP -> V NP | VP PP. DT -> 'a' | 'the'. N -> 'child' | 'cake' | 'fork'. PRP -> 'with' | 'to'. 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. -. 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. 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. 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. Smoothing. If the vocabulary size is |V|=1M. Too many parameters to estimate even a unigram model. MLE assigns values of 0 to unseen (yet not impossible) data. Let alone bigram or trigram models. Smoothing (regularization).

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