Paper Abstract and Keywords |
Presentation |
2010-05-20 11:00
Query Reformulation Type Classification using Query Log Jennifer Pidgeon, Yuichiro Sekiguchi, Tomohiro Tanaka, Tadasu Uchiyama (NTT), Shigeru Fujimura, Takayoshi Mochizuki, Tomoya Suzuki (NTT Resonant) LOIS2010-2 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Most web search engines today recommend more specific queries to users based on their current query. We think important query search information can come from looking at previous queries and seeing how the user reformulates their next query to find the results they are looking for. Our work aims to predict one of five given reformulation types between sequential query pairs. We use a support vector machine algorithm which utilizes features that analyze each query and the correlation between previous and post queries. In addition, we add characteristic classifiers which focus on only two reformulation types and finding distinct differences between them to aid the SVM algorithm predictions. Using both of these methods together produces 83% precision. The ability to predict the type of query a user will input next based on their searching history will lead the way for better query recommendation in web search engines. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Query Classification / Query Log / Web Search / Data Mining / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 110, no. 42, LOIS2010-2, pp. 7-12, May 2010. |
Paper # |
LOIS2010-2 |
Date of Issue |
2010-05-13 (LOIS) |
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 |
LOIS2010-2 |
|