From Atoms to the Solar System: Generating Lexical Analogies from Text

Computer Science;lexical analogy;relational similarity;natural language processing;machine learning

Chiu, Pei-Wen Andy

University of Waterloo

关键词: Computer Science;    lexical analogy;    relational similarity;    natural language processing;    machine learning;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/2943/1/pachiu2006.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

A lexical analogy is two pairs of words (w₁, w₂) and (w₃, w₄) such that the relation between w₁ and w₂ is identical or similar to the relation between w₃ and w₄.For example, (abbreviation, word) forms a lexical analogy with (abstract, report), 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: relational similarity.Lexical analogies are also of practical importance in many applications, including text-understanding and learning ontological relations.

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 dependency grammar 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%.