PPT-Measuring Word Relatedness Using Heterogeneous Vector Space

Scott Wentau Yih Microsoft Research Joint work with Vahed Qazvinian University of Michigan Measuring Semantic Word Relatedness How related are words movie and popcorn. relatedness and diversification. Ron Boschma. Center of . Innovation. , Research and . Competence. in the . Learning. . Economy. (CIRCLE), . Lund. . University. Urban and Regional research centre Utrecht . Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. Ciro . Cattuto. , Dominik Benz, Andreas . Hotho. , . Gerd. . Stumme. Presented by. Smitashree. . Choudhury. Overview. Motivation. Measures of . semantic Relatedness. Semantic . Grounding of measures. Prepared by Vince Zaccone. For Campus Learning Assistance Services at UCSB. Prepared by Vince Zaccone. For Campus Learning Assistance Services at UCSB. Definition: . A . vector space. is a nonempty set . Gavin Band. Why do PCA?. PCA is good at detecting “directions” of major variation in your data. This might be:. Population structure – subpopulations having different allele frequencies.. Unexpected (“cryptic”) relationships.. The matrix . C. has . M. rows and . N. columns, . M. < . N. If we have set this up correctly, the rows of . C. are independent. Nonholonomic (including the pseudo ones) constraints. (If not, do a row reduction and rewrite the constraints) . . Annotators. “. Diego Maradona won against Mexico. ”. Dictionary of terms. against. Diego. Maradona. Mexico. won. 2.2. 5.1. 9.1. 1.0. 0.1. Term Vector. Similarity(. v,w. ) ≈ . cos(. a. ). . t. Lexical Semantics. 2. Information Retrieval System. IR. System. Query String. Document. corpus. Ranked. Documents. 1. Doc1. 2. Doc2. 3. Doc3. .. .. The Vector-Space Model. Graphic Representation. INTRODUCTION. An approach for classification that was developed in the computer science community in the 1990s.. Generalization of a classifier called the Maximal Margin Classifier.. HYPERPLANE. In a . Scott Wen-tau Yih . (Microsoft Research). Joint work with. . Vahed Qazvinian . (University of . Michigan). Measuring Semantic Word Relatedness. How related are words “movie” and “popcorn”?. Ladislav Gallay. Supervisor. : Ing. Marián Šimko, PhD.. Slovak University of Technology. Faculty of Informatics and Information Technologies . Lemmatization. basic form of a word. : . houses . > . Why vector models of meaning?. computing the similarity between words. “. fast. ” is similar to “. rapid. ”. “. tall. ” is similar to “. height. ”. Question answering:. Q. : “. How . Mechanical and biological vectors. A vector is an animal that carries a disease from host to host .. . Mechanical vectors. An animals that carries a pathogen from host to host without being infected itself is a mechanical vector .. Many slides in this section are adapted from Prof. Joydeep Ghosh (UT ECE) who in turn adapted them from Prof. Dik Lee (Univ. of Science and Tech, Hong Kong). 1. These notes are based, in part, on notes by Dr. Raymond J. Mooney at the University of Texas at Austin. .