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| Presentation | 2016-06-04 16:50 Identification of Tweets that Mention Books -- Effects of Features, Data Size, and ML Algorithms -- Shuntaro Yada, Kyo Kageura (UTokyo)  TL2016-7 NLC2016-7 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We report performances of a classifier that identify Tweets that Mention Books (TMB) from tweets that contain the same strings as book titles in Japanese. The classifier we developped performed reasonably good in terms of F1-measure (about 0.7) with the combination of Maximum Entropy Modelling and a Bag-of-Words based feature set. In this paper, in order to improve our classifier, we analyse effects to classification performance, of (1) training data augmentation using a simple search based method with book/reading related keywords, and of (2) feature dimension reduction via Latent Semantic Analysis (LSA). In addition, we compare our classifier to Maltilayer Perceptron activated by Sigmoid function in terms of feature dimension reduction on a trial basis. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Twitter / Named Entity Recognition / Classification / Logistic Regression / Maximum Entropy Modelling / Multilayer Perceptron / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 78, NLC2016-7, pp. 29-34, June 2016. | |
| Paper # | NLC2016-7 | |
| Date of Issue | 2016-05-28 (TL, NLC) | |
| ISSN | Print edition: ISSN 0913-5685 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) | |
| Download PDF | TL2016-7 NLC2016-7 |
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| Conference Information | |
| Committee | NLC TL |
| Conference Date | 2016-06-04 - 2016-06-05 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Otaru University of Commerce |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Application of natural language proessing and linguistic analysis, and general topic of NLP |
| Paper Information | |
| Registration To | NLC |
| Conference Code | 2016-06-NLC-TL |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Identification of Tweets that Mention Books |
| Sub Title (in English) | Effects of Features, Data Size, and ML Algorithms |
| Keyword(1) | |
| Keyword(2) | Named Entity Recognition |
| Keyword(3) | Classification |
| Keyword(4) | Logistic Regression |
| Keyword(5) | Maximum Entropy Modelling |
| Keyword(6) | Multilayer Perceptron |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Shuntaro Yada |
| 1st Author's Affiliation | The University of Tokyo (UTokyo) |
| 2nd Author's Name | Kyo Kageura |
| 2nd Author's Affiliation | The University of Tokyo (UTokyo) |
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| Speaker | Author-1 |
| Date Time | 2016-06-04 16:50:00 |
| Presentation Time | 25 minutes |
| Registration for | NLC |
| Paper # | TL2016-7, NLC2016-7 |
| Volume (vol) | vol.116 |
| Number (no) | no.77(TL), no.78(NLC) |
| Page | pp.29-34 |
| #Pages | 6 |
| Date of Issue | 2016-05-28 (TL, NLC) |
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