PDF-Measures of Distributional Similarity

Lee Department of Computer Science Cornell University Ithaca NY 148537501 cornell edu We study distributional similarity measures for the purpose of improving probability estima tion for unseen c. 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 . Bamshad Mobasher. DePaul University. Distance or Similarity Measures. Many data mining and analytics tasks involve the comparison of objects and determining . their . similarities (or dissimilarities). Input for Multidimensional Scaling and Clustering. Distances and Similarities. Both are ways of measuring how similar two objects are. Distances increase as objects are less similar. The distance of an object to itself is 0. 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. 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. Word . Similarity: . Distributional Similarity (I). Problems with thesaurus-based . meaning. We don’t have a thesaurus for every language. Even if we do, . they have problems with . recall. M. any . 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. Case-based reasoning. Introduction. Common term in everyday language, where two objects usually are considered similar if they look or sound similar. Similarity is a core concept within CBR. From a CBR perspective: «Two problems are similar if they have similar solutions». CSE, HKUST. March 20. Recap. String declaration. str1=“Hong”. str2=“Kong”. String Operators. strr. =str1+str2. “H” in . strr. String Slicing. strr. [. i. ]. strr. [:. i. ]. strr. [. i. :]. 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. . S. imilarity to Semantic Relations. Georgeta. . Bordea. , November 25. Based on a talk by Alessandro . Lenci. . titled “Will DS ever become Semantic?”, Jan 2014. Distributional Semantics . (DS. Bamshad Mobasher. DePaul University. Distance or Similarity Measures. Many data mining and analytics tasks involve the comparison of objects and determining in terms of their similarities (or dissimilarities). 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. .