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Paper Abstract and Keywords
Presentation 2016-11-04 11:30
Web Service Clustering through Calculating Semantic Similarity of Web Services using Novel Ontology Learning Method
Rupasingha Arachchilage Hiruni Madhusha Rupasingha, Incheon Paik (UOA), Banage Thenne Gedara Samantha Kumara (SUSL) SC2016-21
Abstract (in Japanese) (See Japanese page) 
(in English) Web service clustering is playing a major role in the efficient Web service discovery and
recommendation. Clustering is depending on grouping similar Web services by calculating similarity values. In
this paper, we propose a Web service clustering method through calculating semantic similarity of Web services
using a novel ontology learning method. New ontology generation is based on the specific terms rather than
general terms. Specific terms are taking a main part when classifying the domain information than general
terms. New ontology filters are introduced for similarity calculation. Information-retrieval based methods used
to manage failure situation of ontology based similarity calculation. Experimental results show the effectiveness
of clustering process comparing with existing approaches.
Keyword (in Japanese) (See Japanese page) 
(in English) Term Specificity / Ontology Learning / Similarity Calculation / Information Retrieval / Web Service Clustering / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 287, SC2016-21, pp. 13-18, Nov. 2016.
Paper # SC2016-21 
Date of Issue 2016-10-28 (SC) 
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 SC2016-21

Conference Information
Committee SC  
Conference Date 2016-11-04 - 2016-11-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Takigawa Memorial Hall, Kobe Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Analysis and Synthesis of Service Design, etc. 
Paper Information
Registration To SC 
Conference Code 2016-11-SC 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Web Service Clustering through Calculating Semantic Similarity of Web Services using Novel Ontology Learning Method 
Sub Title (in English)  
Keyword(1) Term Specificity  
Keyword(2) Ontology Learning  
Keyword(3) Similarity Calculation  
Keyword(4) Information Retrieval  
Keyword(5) Web Service Clustering  
Keyword(6)  
Keyword(7)  
Keyword(8)  
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)
3rd Author's Name Banage Thenne Gedara Samantha Kumara  
3rd Author's Affiliation Sabaragamuwa University of Sri Lanka (SUSL)
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Speaker Author-1 
Date Time 2016-11-04 11:30:00 
Presentation Time 25 minutes 
Registration for SC 
Paper # SC2016-21 
Volume (vol) vol.116 
Number (no) no.287 
Page pp.13-18 
#Pages 6 
Date of Issue 2016-10-28 (SC) 

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