Paper Abstract and Keywords |
Presentation |
2019-09-28 17:30
Estimating Distributed Expressions of Unknown Compound Word Using Distributed Expressions of Known Words Ryota Takagi, Kazuhiro Kazama (Wakayama Univ), Takeshi Sakaki (Hotto Link) NLC2019-27 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, the distributed expression, which treats the meaning of a word as a low-dimensional vector expression, is widely used. There are various methods to obtain the distributed expression of a word. For example, Mikolov et al. proposed word2vec that learns the surrounding words of a word by a neural network, and outputs the vector of weights in the middle layer of the learning result as a distributed representation, However, an unknown compound word should be re-learn even if it is a known word sequences because only distributed repre- sentations of words, which are used for learning, are available in word2vec. It requires a lot of additional cost. We propose a method to estimate the distributed expression of unknown compound words with relatively high accuracy, using distributed expression data that has been already learned and a simple statistical indicator. In practice, we focus on the modification relation between nouns that constitute a Japanese compound words and weight distributed expression vectors by compound noun frequency of noun 2-grams. Additionally, we compare the similarity and the MRR of the proposed method with those of other methods that are used to obtain the distributed expression of a sentence using the distributed expression of words such as the simple average method and the method proposed by Arora et al. etc. We show the effectiveness of the proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
compound words / distributed representation / word2vec / compound noun frequency / modification relation / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 212, NLC2019-27, pp. 103-108, Sept. 2019. |
Paper # |
NLC2019-27 |
Date of Issue |
2019-09-20 (NLC) |
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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NLC2019-27 |
Conference Information |
Committee |
NLC IPSJ-DC |
Conference Date |
2019-09-27 - 2019-09-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Future Corporation |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
The Thirteenth Text Analytics Symposium |
Paper Information |
Registration To |
NLC |
Conference Code |
2019-09-NLC-DC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Estimating Distributed Expressions of Unknown Compound Word Using Distributed Expressions of Known Words |
Sub Title (in English) |
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compound words |
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distributed representation |
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word2vec |
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compound noun frequency |
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modification relation |
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1st Author's Name |
Ryota Takagi |
1st Author's Affiliation |
Wakayama University (Wakayama Univ) |
2nd Author's Name |
Kazuhiro Kazama |
2nd Author's Affiliation |
Wakayama University (Wakayama Univ) |
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Takeshi Sakaki |
3rd Author's Affiliation |
Hotto Link Inc. (Hotto Link) |
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Speaker |
Author-1 |
Date Time |
2019-09-28 17:30:00 |
Presentation Time |
25 minutes |
Registration for |
NLC |
Paper # |
NLC2019-27 |
Volume (vol) |
vol.119 |
Number (no) |
no.212 |
Page |
pp.103-108 |
#Pages |
6 |
Date of Issue |
2019-09-20 (NLC) |
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