Paper Abstract and Keywords |
Presentation |
2020-03-11 10:10
Sentence Visualization Based on Relative Sentence Embeddings Haruya Ishizuka (Bridgestone Corp.), Daichi Mochihashi (ISM) IBISML2019-42 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Sentence visualization is important for a organization, such as company or government, since it facilitates to understand underlying semantics within accumulated text collection. SIF vector (Arora et al., ICLR, 2017) estimated from pre-trained word vectors is a sentence vector which reflects sentence-specific information, and leveraging this data representation is one of effective approaches for this task. In this paper, we propose Relative Sentence Embeddings (RSEs) which are a novel sentence representation computed from SIF vectors and a visualization method based on this representation. RSEs are logarithmic transformation of mixing rates estimated by applying Gaussian mixture models to a set of SIF vectors. Visual coordinates are obtained by dimension reduction over RSEs via t-SNE. Utilizing properties of high-dimensional Gaussian distribution, we prove that these coordinates have higher cluster separacity than the
ones based on naive dimension reduction over SIF vectors. Experimental result shows our theoretical result is held in a real world dataset. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Text Visualization / Semantic Visualization / pre-trained word vectors / Sentence Embeddings / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 476, IBISML2019-42, pp. 63-70, March 2020. |
Paper # |
IBISML2019-42 |
Date of Issue |
2020-03-03 (IBISML) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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IBISML2019-42 |
Conference Information |
Committee |
IBISML |
Conference Date |
2020-03-10 - 2020-03-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kyoto University |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Machine learning, etc. |
Paper Information |
Registration To |
IBISML |
Conference Code |
2020-03-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Sentence Visualization Based on Relative Sentence Embeddings |
Sub Title (in English) |
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Keyword(1) |
Text Visualization |
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Semantic Visualization |
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pre-trained word vectors |
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Sentence Embeddings |
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1st Author's Name |
Haruya Ishizuka |
1st Author's Affiliation |
Bridgeston Corporation (Bridgestone Corp.) |
2nd Author's Name |
Daichi Mochihashi |
2nd Author's Affiliation |
The Institute of Statistical Mathematics (ISM) |
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Speaker |
Author-1 |
Date Time |
2020-03-11 10:10:00 |
Presentation Time |
25 minutes |
Registration for |
IBISML |
Paper # |
IBISML2019-42 |
Volume (vol) |
vol.119 |
Number (no) |
no.476 |
Page |
pp.63-70 |
#Pages |
8 |
Date of Issue |
2020-03-03 (IBISML) |
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