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| Presentation | 2011-01-25 10:30 Early Topic Detection from Topic Frequency Transition with Semi-supervised Learning Hiroyoshi Takahashi (Kobe Univ.), Yoshiaki Yasumura (Shibaura IT), Kuniaki Uehara (Kobe Univ.)  KBSE2010-40 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This report presents a method for early potential topic detection from blog articles. Potential topic is defined as a phrase which has potential to spread through many blogs. To discover potential topics, this method learns from topic frequency transitions in blog articles. Though this learning requires sufficient amount of labeled data, labeling data is costly and time consuming. Therefore this method employs a semi-supervised learning to reduce labeling cost. First, this method extracts candidates of potential topics from categorized blog articles. To detect potential topics from the candidates, a classifier is built from topic frequency transition. The experimental results with real data show the effectiveness of the proposed method. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | semi-supervised learning / burst detection / blog / early-detection / focused topic / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 110, no. 386, KBSE2010-40, pp. 31-36, Jan. 2011. | |
| Paper # | KBSE2010-40 | |
| Date of Issue | 2011-01-17 (KBSE) | |
| 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 | KBSE2010-40 |
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| Conference Information | |
| Committee | KBSE |
| Conference Date | 2011-01-24 - 2011-01-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kikai-Shinko-Kaikan Bldg. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Knowledge-Based Software Engineering, etc. |
| Paper Information | |
| Registration To | KBSE |
| Conference Code | 2011-01-KBSE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Early Topic Detection from Topic Frequency Transition with Semi-supervised Learning |
| Sub Title (in English) | |
| Keyword(1) | semi-supervised learning |
| Keyword(2) | burst detection |
| Keyword(3) | blog |
| Keyword(4) | early-detection |
| Keyword(5) | focused topic |
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| 1st Author's Name | Hiroyoshi Takahashi |
| 1st Author's Affiliation | Kobe University (Kobe Univ.) |
| 2nd Author's Name | Yoshiaki Yasumura |
| 2nd Author's Affiliation | Shibaura Institute of Technology (Shibaura IT) |
| 3rd Author's Name | Kuniaki Uehara |
| 3rd Author's Affiliation | Kobe University (Kobe Univ.) |
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| Speaker | Author-1 |
| Date Time | 2011-01-25 10:30:00 |
| Presentation Time | 45 minutes |
| Registration for | KBSE |
| Paper # | KBSE2010-40 |
| Volume (vol) | vol.110 |
| Number (no) | no.386 |
| Page | pp.31-36 |
| #Pages | 6 |
| Date of Issue | 2011-01-17 (KBSE) |
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