PPT-Word Meaning and Similarity

Word Senses and Word Relations Reminder 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. 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. Set 10. Lexical Relations. s. lides adapted from Dan . Jurafsky. and Bill . MacCartney. Three. levels of . m. eaning. Lexical . Semantics (words). Sentential . / Compositional / Formal Semantics. Discourse . Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. 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 . Instructor: Paul Tarau, based on . Rada. . Mihalcea’s. original slides. Note. : Some of the material in this slide set was adapted from a tutorial given by . Rada. . Mihalcea. & Ted Pedersen at ACL 2005. 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. 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 . computing the similarity between words. “. fast. ” is similar to “. rapid. ”. “. tall. ” is similar to “. height. ”. Question answering:. Q. : “. How . tall. . is Mt. Everest?”. Candidate A: “The . s. lides adapted from Dan . Jurafsky. and Bill . MacCartney. Three. levels of . m. eaning. Lexical . Semantics (words). Sentential / Compositional / Formal Semantics. Discourse . or Pragmatics. m. eaning + context + world knowledge. 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. 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. .