PPT-Word Similarity David Kauchak

CS159 Fall 2014 Admin Assignment 4 Quiz 2 Thursday Same rules as quiz 1 First 30 minutes of class Open book and notes Assignment 5 out on Thursday Quiz 2 Topics Linguistics 101 Parsing. 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 . Word Senses. . and Word Relations. Terminology: lemma and . wordform. A . lemma. or . citation . form. Same . stem, part of speech, rough . semantics. A . wordfor. m. The inflected word as it appears in text. 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:. Corpora and Statistical Methods. Part 1. Semantic . similarity. and the vector space model. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. WordNet. Lubomir. . Stanchev. Example . Similarity Graph. Dog. Cat. 0.3. 0.3. Animal. 0.8. 0.2. 0.8. 0.2. Applications. If we type . automobile. . in our favorite Internet search engine, for example Google or Bing, then all top results will contain the word . Focus on . word and sentence . similarity. Formal side: define similarity in principle. Characterizing word meaning . in context. Given a word in a particular sentence context: Can we characterize its meaning without reference to dictionary senses?. 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. Dan Jurafsky. Stanford University. Introduction and Course Overview. What is Computational Lexical Semantics. Any computational process involving word meaning!. Computing . Word Similarity . Distributional (Vector) Models of . How many items are on the kitchen table?. What sort of man do you think Hannah’s father is?. Why has Anthony Browne chosen blue for the kitchen?. Taken from Gorilla by Anthony Browne. What does the word ‘confusion’ mean?. Word Senses. . and Word Relations. Terminology: lemma and . wordform. A . lemma. or . citation . form. Same . stem, part of speech, rough . semantics. A . wordfor. m. The inflected word as it appears in text. Quiz. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. 3. Deer-mouse. 4. Deer-roof. Quiz Answer. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. CS159 – Spring 2011. Administrivia. Assignment 0 due today. article discussion. Assignment 1 out soon. due Wednesday, 2/2 in class. no code submitted, but will require coding. Send me an e-mail if you’d like me to e-mail announcements to another account besides your school account.