Geometry of compositionality

Word embedding is a popular representation of words in vector space, and its geometry reveals the lexical semantics. This thesis further explores the interesting geometric properties of word embedding, and looks into its interaction with the context representation. We propose an innovative method to detect whether a given word or phrase is used literally in a specific context. This work focuses on three specific applications in natural language processing: idiomaticity, sarcasm and metaphor detection. Extensive experiments have shown that this embedding-based method achieves good performance in multiple languages.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2017

Author dc:creator

• Gong, Hongyu

Contributors dc:contributor

• Viswanath, Pramod
• Bhat, Suma

• Compositionality detection

Statement dc:rights

• Copyright 2017 Hongyu Gong

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/98362

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/98362