dc.contributor.author | Chiu, Pei-Wen Andy | en |
dc.date.accessioned | 2007-05-08 14:01:50 (GMT) | |
dc.date.available | 2007-05-08 14:01:50 (GMT) | |
dc.date.issued | 2006 | en |
dc.date.submitted | 2006 | en |
dc.identifier.uri | http://hdl.handle.net/10012/2943 | |
dc.description.abstract | A <em>lexical analogy</em> is two pairs of words (<em>w</em><sub>1</sub>, <em>w</em><sub>2</sub>) and (<em>w</em><sub>3</sub>, <em>w</em><sub>4</sub>) such that the relation between <em>w</em><sub>1</sub> and <em>w</em><sub>2</sub> is identical or similar to the relation between <em>w</em><sub>3</sub> and <em>w</em><sub>4</sub>. For example, (<em>abbreviation</em>, <em>word</em>) forms a lexical analogy with (<em>abstract</em>, <em>report</em>), because in both cases the former is a shortened version of the latter. Lexical analogies are of theoretic interest because they represent a second order similarity measure: <em>relational similarity</em>. Lexical analogies are also of practical importance in many applications, including text-understanding and learning ontological relations. <BR> <BR> This thesis presents a novel system that generates lexical analogies from a corpus of text documents. The system is motivated by a well-established theory of analogy-making, and views lexical analogy generation as a series of three processes: identifying pairs of words that are semantically related, finding clues to characterize their relations, and generating lexical analogies by matching pairs of words with similar relations. The system uses a <em>dependency grammar</em> to characterize semantic relations, and applies machine learning techniques to determine their similarities. Empirical evaluation shows that the system performs remarkably well, generating lexical analogies at a precision of over 90%. | en |
dc.format | application/pdf | en |
dc.format.extent | 1245807 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | University of Waterloo | en |
dc.rights | Copyright: 2006,
Chiu, Pei-Wen Andy. All rights reserved. | en |
dc.subject | Computer Science | en |
dc.subject | lexical analogy | en |
dc.subject | relational similarity | en |
dc.subject | natural language processing | en |
dc.subject | machine learning | en |
dc.title | From Atoms to the Solar System: Generating Lexical Analogies from Text | en |
dc.type | Master Thesis | en |
dc.pending | false | en |
uws-etd.degree.department | School of Computer Science | en |
uws-etd.degree | Master of Mathematics | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Unreviewed | en |
uws.scholarLevel | Graduate | en |