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Paper Abstract and Keywords
Presentation 2013-07-23 10:40
Improving Pseudo-Relevance Feedback via Microblog Document Selection
Taiki Miyanishi, Kazuhiro Seki, Kuniaki Uehara (Kobe Univ.) DE2013-21
Abstract (in Japanese) (See Japanese page) 
(in English) Query expansion method using pseudo-relevance feedback is significantly effective for microblog search because the query expansion method can solve the vocabulary mismatch problem when searching short documents such as twitter messages (i.e. tweet) limited to 140 characters of content. The pseudo-relevance feedback approaches assume that the top ranked documents in the initial search results are relevant, which contain good topic-related words for relevance feedback. However, that assumption is often invalid because the initial search results may largely contain non-relevant documents and only a small share of the suggested expansion words are useful. Many others are either harmful or useless. To overcome the limitation of pseudo-relevance feedback for microblog search, we pro- pose novel query expansion method based on two-stage relevance feedback frameworks modeling search interests by manual tweet selection and integrating lexical and temporal evidence into its relevance model. Our experiments on a corpus of microblog data (Tweets2011 corpus) show that our two-stage relevance feedback approaches considerably improve search result relevance without decreasing retrieval over almost all topics.
Keyword (in Japanese) (See Japanese page) 
(in English) Twitter / Microblog Search / Pseudo-Relevance Feedback / Query Expansion / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 150, DE2013-21, pp. 83-88, July 2013.
Paper # DE2013-21 
Date of Issue 2013-07-15 (DE) 
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 DE2013-21

Conference Information
Committee DE IPSJ-DBS IPSJ-IFAT  
Conference Date 2013-07-22 - 2013-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Data Management, Information Search and Knowledge Retrieval for Big Data, etc. 
Paper Information
Registration To DE 
Conference Code 2013-07-DE-DBS-IFAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving Pseudo-Relevance Feedback via Microblog Document Selection 
Sub Title (in English)  
Keyword(1) Twitter  
Keyword(2) Microblog Search  
Keyword(3) Pseudo-Relevance Feedback  
Keyword(4) Query Expansion  
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Keyword(6)  
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1st Author's Name Taiki Miyanishi  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Kazuhiro Seki  
2nd Author's Affiliation Kobe University (Kobe Univ.)
3rd Author's Name Kuniaki Uehara  
3rd Author's Affiliation Kobe University (Kobe Univ.)
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Speaker Author-1 
Date Time 2013-07-23 10:40:00 
Presentation Time 30 minutes 
Registration for DE 
Paper # DE2013-21 
Volume (vol) vol.113 
Number (no) no.150 
Page pp.83-88 
#Pages 6 
Date of Issue 2013-07-15 (DE) 

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