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Paper Abstract and Keywords
Presentation 2024-09-12 10:55
Evaluation of subtopic presentation using a large-scale language model for exploratory information retrieval
Tappei Horikawa, Daisuke Kitayama (Kogakuin Univ.) DE2024-8
Abstract (in Japanese) (See Japanese page) 
(in English) There is a search task called an Recall-oriented tasks, in which exhaustive information is collected to solve a problem for which a decision is made after comparisons are made.
In recall-oriented tasks, users often lack prior knowledge, and it is not easy to ensure the comprehensiveness of information because of the challenges of devising termination goals and queries.
In this study, we propose a method for presenting hints about search topics in an recall-oriented tasks, with the goal of enabling the user to hold on to the main contents.
These hints are subtopics related to the search topic and their explanations, and they point to the main viewpoints from which users can comprehensively collect information.
By generating these hints using a large-scale language model, we verify the applicability of our method without constructing a dataset with previously researched and collected subtopics.
Experimental results using a search system with a hinting function showed that the search query logs were judged to be more exhaustive when hints were provided.
Keyword (in Japanese) (See Japanese page) 
(in English) Information Retrieval / Recall-Oriented Tasks / Subtopic Presentation / Large-scale Language Model / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 185, DE2024-8, pp. 25-30, Sept. 2024.
Paper # DE2024-8 
Date of Issue 2024-09-04 (DE) 
ISSN 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 DE2024-8

Conference Information
Committee DE IPSJ-DBS IPSJ-IFAT  
Conference Date 2024-09-11 - 2024-09-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Awaji Yumebutai 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Bigdata management, information retrieval, knowledge discovery, etc. 
Paper Information
Registration To DE 
Conference Code 2024-09-DE-DBS-IFAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of subtopic presentation using a large-scale language model for exploratory information retrieval 
Sub Title (in English)  
Keyword(1) Information Retrieval  
Keyword(2) Recall-Oriented Tasks  
Keyword(3) Subtopic Presentation  
Keyword(4) Large-scale Language Model  
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1st Author's Name Tappei Horikawa  
1st Author's Affiliation Kogakuin University (Kogakuin Univ.)
2nd Author's Name Daisuke Kitayama  
2nd Author's Affiliation Kogakuin University (Kogakuin Univ.)
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Speaker Author-1 
Date Time 2024-09-12 10:55:00 
Presentation Time 25 minutes 
Registration for DE 
Paper # DE2024-8 
Volume (vol) vol.124 
Number (no) no.185 
Page pp.25-30 
#Pages 6 
Date of Issue 2024-09-04 (DE) 

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