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Brian K. Smith. Hiyakumoto, Laurie Satsue, 1969- Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2011-03-07T15:11:21Z 2011-03-07T15:11:21Z 1999 1999 http://hdl.handle.net/1721.1/61537 42722519 Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1999. Includes bibliographical references (leaves 77-80). Although metaphor is generally recognized as an integral component of everyday language, very few computational systems capable of understanding metaphoric utterances exist today. This thesis describes one approach to the problem and presents PoEM, a prototype system which recognizes and interprets metaphoric descriptions of emotions and mental states in single-sentence input. Building upon previous work in knowledge-based metaphor comprehension, this research adopts a goal-driven approach which assumes each metaphor is selected by a speaker for its aptness at serving a particular communicative goal. To identify these goals, an empirical analysis of metaphor distribution in song lyrics was performed, and typical communicative intentions and surface patterns were identified for the top five most frequently occurring metaphor groups. These intentions and surface patterns have been implemented as a set of metaphor templates and interpretation rules in PoEM, using the WordNet lexical database for supplemental semantic information. Evaluation of PoEM demonstrates fairly high accuracy but low recall. Laurie Satsue Hiyakumoto. S.M. 80 leaves eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Architecture. Program in Media Arts and Sciences PoEM : a parser of emotion metaphors Parser of emotion metaphors Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="85c1ee8c-d1be-410d-8216-8ad2a7a455b3"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>PoEM : a parser of emotion metaphors</Title> <Subtitle>Parser of emotion metaphors</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>1999</PublicationDate> <Authors> <Author> <DisplayName>Hiyakumoto, Laurie Satsue, 1969-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Architecture. Program in Media Arts and Sciences</Keyword> <Abstract>Although metaphor is generally recognized as an integral component of everyday language, very few computational systems capable of understanding metaphoric utterances exist today. This thesis describes one approach to the problem and presents PoEM, a prototype system which recognizes and interprets metaphoric descriptions of emotions and mental states in single-sentence input. Building upon previous work in knowledge-based metaphor comprehension, this research adopts a goal-driven approach which assumes each metaphor is selected by a speaker for its aptness at serving a particular communicative goal. To identify these goals, an empirical analysis of metaphor distribution in song lyrics was performed, and typical communicative intentions and surface patterns were identified for the top five most frequently occurring metaphor groups. These intentions and surface patterns have been implemented as a set of metaphor templates and interpretation rules in PoEM, using the WordNet lexical database for supplemental semantic information. Evaluation of PoEM demonstrates fairly high accuracy but low recall.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>