PPT-Distributional models

Katrin Erk You can get an idea of what a word means from observing it in context He filled the wampimuk passed it around and we all drank some We found a little hairy wampimuk sleeping behind a tree . The ARMApq series is generated by 12 pt pt 12 qt 949 949 949 Thus is essentially the sum of an autoregression on past values of and a moving average o tt t white noise process Given together with starting values of the whole series se 1 Introduction Distributional approaches to meaning acquisition utilize distributional proper ties of linguistic entities as the building blocks of semantics In doing so they rely fundamentally on a set of assumptions about the nature of language Similarity. David Kauchak. CS159 Fall 2014. Admin. Assignment 5 out. Word similarity. How similar are two words?. sim(w. 1. , w. 2. ) = . ?. ?. score:. rank:. w. w. 1. w. 2. w. 3. list: w. 1. . and . in Climate Policy: . Co-Benefits, Carbon Rent and Adaptation. . James K. Boyce. Department of Economics & Political Economy Research Institute. University of Massachusetts, . Amherst. Advanced Graduate Workshop on Development & Globalization. A Microsimulation Approach. Poverty Reduction and Equity Group. Poverty Reduction and Economic Management Network. World Bank. April 2011. Outline. Background. Approach. Model. Basic structure and data requirements.  . Ian Gough. CASE, LSE. Goals of paper. Contemporary policies to reduce emissions of greenhouse gases. will have distributive . consequences. Thus . implications for the scope and remit of . ‘social policy’. . Thisarticleconsiderstheproblemofassessingthedistributionalconsequencesofatreatmentonsomeoutcomevariableofinterestwhentreatmentintakeis(possibly)nonrandomized,butthereisabinaryinstrumentavailableforthe Katrin Erk. University of Texas at . Austin. Meaning in Context Symposium. München. September 2015. Joint work with Gemma . Boleda. Semantic features by example: . Katz & Fodor. Different meanings of a word characterized by lists of semantic features. 1.2DiscussionIs(multi-distributional)deniabilityuseful?Theidealdeniableencryptionschemewouldbenoninter-activeandfullydeniableforbothparties.Unfortunately,ithasbeenrecentlyshown[BNNO11]thatthesepropert Word Association and Similarity. Ido Dagan. Including Slides by:. . Katrin. Erk (mostly), Marco Baroni,. Alessandro Lenci (BLESS). 2. Word Association Measures. Goal: measure the statistical strength of word (term) co-occurrence in corpus. Stéphane. Verguet. Email: . verguet@hsph.harvard.edu. April 18, 2017, WBG/IMF Spring Meetings, Washington, DC. Tax is the single most effective tobacco control policy. France: cigarette consumption & inflation-adjusted price . SEMANTICS. Heng. . Ji. jih@rpi.edu. September 29, 2016. Word Similarity & Relatedness. How similar is . pizza. to . pasta. ?. How related is . pizza. . to . Italy. ?. Representing words as vectors. Erk. You can get an idea of what a word means from observing it in context. He filled the . wampimuk. , passed it around, and we all drank some. We found a little hairy . wampimuk. . sleeping behind a tree. . Distributional Semantic Models in Lexical Typology: Constructing a typological questionnaire Daria Ryzhova School of Linguistics NRU HSE Outline Lexical Typology: Frame-based Approach Ideology Typological questionnaire Constructing a