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Paper Abstract and Keywords
Presentation 2018-11-09 11:30
Evaluation of the Effectiveness of Recommendation while Managing the Data Density of the Web Service-User Preference
Rupasingha Arachchilage Hiruni Madhusha Rupasingha, Incheon Paik (UOA) KBSE2018-30 SC2018-25
Abstract (in Japanese) (See Japanese page) 
(in English) Recommender systems become important in the research and commercial society, where many recommendation
solutions have been suggested for the providing predictions. These solutions typically perform differently in various methods
and datasets. In this paper, we deal with Web service recommendation to discover applicable services quickly and accurately
using a collaborative filtering (CF) technique which suffers from data sparsity and cold-start problems. We manage the density
of Web service-user preference using a novel ontology-based clustering approach that used domain specificity and service
similarity for the ontology generation. Using an evaluation we identified this approach can easily and effectively increase the
data density of the user-service dataset by the deal with non-rated user preferences based on the user?s past preferred domains.
Then user ratings are predicted based on the trust value between users by calculating the correlation of users. Evaluations are
based on the different sparsity alleviating methods and ontology generation, and it shows proposed method effectively and
efficiently reaches lower prediction error comparing with existing approaches.
Keyword (in Japanese) (See Japanese page) 
(in English) Recommendation / Collaborative Filtering / Web Services / Ontology Learning / Cold-Start / Sparsity / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 293, SC2018-25, pp. 13-18, Nov. 2018.
Paper # SC2018-25 
Date of Issue 2018-11-02 (KBSE, SC) 
ISSN Online edition: ISSN 2432-6380
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 KBSE2018-30 SC2018-25

Conference Information
Committee KBSE SC  
Conference Date 2018-11-09 - 2018-11-10 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SC 
Conference Code 2018-11-KBSE-SC 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of the Effectiveness of Recommendation while Managing the Data Density of the Web Service-User Preference 
Sub Title (in English)  
Keyword(1) Recommendation  
Keyword(2) Collaborative Filtering  
Keyword(3) Web Services  
Keyword(4) Ontology Learning  
Keyword(5) Cold-Start  
Keyword(6) Sparsity  
1st Author's Name Rupasingha Arachchilage Hiruni Madhusha Rupasingha  
1st Author's Affiliation University of Aizu (UOA)
2nd Author's Name Incheon Paik  
2nd Author's Affiliation University of Aizu (UOA)
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Speaker Author-1 
Date Time 2018-11-09 11:30:00 
Presentation Time 30 minutes 
Registration for SC 
Paper # KBSE2018-30, SC2018-25 
Volume (vol) vol.118 
Number (no) no.292(KBSE), no.293(SC) 
Page pp.13-18 
Date of Issue 2018-11-02 (KBSE, SC) 

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