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| Presentation | 2012-11-07 15:30 Feature Selection for LDA using Bayesian Network Ryosuke Ohata, Maomi Ueno (Univ. of Electro-Communications)  IBISML2012-53 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Recently there has been great interest in topic model analyzing discrete data accompanied by arbitrary features, such as authors. However, previous work in such topic modeling does not take account of feature selection. This paper presents a feature selection method for such topic model. The proposed method selects the feature set involving data generation by clarifying causality between the latent topic and features using bayesian network-based approach. The Advantages of the proposed method are as follows: First, computational time is short because the proposed method can select the feature set without learning latent topic of any combination of features. Second, feature selection accuracy is high because the proposed method has consistency. We demonstrate the effectiveness of the proposed method by simulation. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | topic model / feature selection / bayesian network / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 279, IBISML2012-53, pp. 135-142, Nov. 2012. | |
| Paper # | IBISML2012-53 | |
| Date of Issue | 2012-10-31 (IBISML) | |
| 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 | IBISML2012-53 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2012-11-07 - 2012-11-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | the 15th Information-Based Induction Sciences Workshop |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2012-11-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Feature Selection for LDA using Bayesian Network |
| Sub Title (in English) | |
| Keyword(1) | topic model |
| Keyword(2) | feature selection |
| Keyword(3) | bayesian network |
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| 1st Author's Name | Ryosuke Ohata |
| 1st Author's Affiliation | University of Electro-Communications (Univ. of Electro-Communications) |
| 2nd Author's Name | Maomi Ueno |
| 2nd Author's Affiliation | University of Electro-Communications (Univ. of Electro-Communications) |
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| Speaker | Author-1 |
| Date Time | 2012-11-07 15:30:00 |
| Presentation Time | 150 minutes |
| Registration for | IBISML |
| Paper # | IBISML2012-53 |
| Volume (vol) | vol.112 |
| Number (no) | no.279 |
| Page | pp.135-142 |
| #Pages | 8 |
| Date of Issue | 2012-10-31 (IBISML) |
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