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| Presentation | 2010-11-04 15:00 [Poster Presentation] An Application of Generalized Linear Model for Recommender System -- Rating Estimation Based on Main-Effect Model -- Yu Fujimoto (Aoyama Gakuin Univ.)  IBISML2010-68 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Collaborative filtering based on a rating matrix is broadly used in recommender systems. In a practical situation, the matrix tends to be sparse when the sets of items and objects are huge. And, sparsity of rating matrices easily deteriorate the accuracy of recommendation. In the regression setup, sparse matrices cause the over-fitting problem, and the number of parameters in a model should be well controlled. In this paper, a simple main-effect model with a small number of parameters is introduced and extended in the framework of the generalized linear model. Even with such a simple model, one can express linearity, independence, and weak special types of non-linearity and dependence between users and objects by introducing a one-parameter family link function. This paper experimentally shows a possibility for improvement of estimation results based on a simple model. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | generalized linear model / collaborative filter / recommender system / linearity / independence / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 110, no. 265, IBISML2010-68, pp. 65-71, Nov. 2010. | |
| Paper # | IBISML2010-68 | |
| Date of Issue | 2010-10-28 (IBISML) | |
| 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 | IBISML2010-68 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2010-11-04 - 2010-11-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | IIS, Univ. of Tokyo |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IBIS 2010 (Workshop on Information-based Induction Sciences) |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2010-11-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Application of Generalized Linear Model for Recommender System |
| Sub Title (in English) | Rating Estimation Based on Main-Effect Model |
| Keyword(1) | generalized linear model |
| Keyword(2) | collaborative filter |
| Keyword(3) | recommender system |
| Keyword(4) | linearity |
| Keyword(5) | independence |
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| 1st Author's Name | Yu Fujimoto |
| 1st Author's Affiliation | Aoyama Gakuin University (Aoyama Gakuin Univ.) |
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| Speaker | Author-1 |
| Date Time | 2010-11-04 15:00:00 |
| Presentation Time | 180 minutes |
| Registration for | IBISML |
| Paper # | IBISML2010-68 |
| Volume (vol) | vol.110 |
| Number (no) | no.265 |
| Page | pp.65-71 |
| #Pages | 7 |
| Date of Issue | 2010-10-28 (IBISML) |
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