The Open UniversitySkip to content
 

Quantum-inspired Complex Word Embedding

Li, Qiuchi; Uprety, Sagar; Wang, Benyou and Song, Dawei (2018). Quantum-inspired Complex Word Embedding. In: Proceedings of the 3rd Workshop on Representation Learning for NLP, Association for Computational Linguistics, pp. 50–57.

Full text available as:
[img]
Preview
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (351kB) | Preview
URL: http://aclweb.org/anthology/W18-3006
Google Scholar: Look up in Google Scholar

Abstract

A challenging task for word embeddings is to capture the emergent meaning or polarity of a combination of individual words. For example, existing approaches in word embeddings will assign high probabilities to the words ”Penguin” and ”Fly” if they frequently co-occur, but it fails to capture the fact that they occur in an opposite sense - Penguins do not fly. We hypothesize that humans do not associate a single polarity or sentiment to each word. The word contributes to the overall polarity of a combination of words depending upon which other words it is combined with. This is analogous to the behavior of microscopic particles which exist in all possible states at the same time and interfere with each other to give rise to new states depending upon their relative phases. We make use of the Hilbert Space representation of such particles in Quantum Mechanics where we subscribe a relative phase to each word, which is a complex number, and investigate two such quantum inspired models to derive the meaning of a combination of words. The proposed models achieve better performances than state-ofthe-art non-quantum models on the binary sentence classification task.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 Association for Computational Linguistics
Project Funding Details:
Funded Project NameProject IDFunding Body
QUARTZNot SetThe Open University (OU)
Extra Information: Hosted by the 56th Annual Meeting of the Association for Computational Linguistics.
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 57675
Depositing User: Sagar Uprety
Date Deposited: 03 Dec 2018 09:39
Last Modified: 03 May 2019 22:13
URI: http://oro.open.ac.uk/id/eprint/57675
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU