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| 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 |
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| 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. |
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| 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 | |
| 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 | KBSE2018-30 SC2018-25 |
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| 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 |
| 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) |
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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 |
| #Pages | 6 |
| Date of Issue | 2018-11-02 (KBSE, SC) |
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