Presentation | 2010-06-14 Collaborative Filtering with A Bayesian Hierarchical Model Hideki ASOH, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Bayesian hierarchical modeling is a very powerful tool for multi-task learning. With the Bayesian hierarchical modeling, parameters of similar systems can be simultaneously estimated stably even when the amount of data per system is small. In this work, a simple Bayesian hierarchical model is applied to the collaborative filtering, a typical multi-task problem. Experimental results with movie and food preference data demonstrate that the model is promising. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | recommender system / preference model / collaborative filtering / Bayesian hierarchical model / multitask learning |
Paper # | IBISML2010-10 |
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Conference Information | |
Committee | IBISML |
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Conference Date | 2010/6/7(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Collaborative Filtering with A Bayesian Hierarchical Model |
Sub Title (in English) | |
Keyword(1) | recommender system |
Keyword(2) | preference model |
Keyword(3) | collaborative filtering |
Keyword(4) | Bayesian hierarchical model |
Keyword(5) | multitask learning |
1st Author's Name | Hideki ASOH |
1st Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST)() |
Date | 2010-06-14 |
Paper # | IBISML2010-10 |
Volume (vol) | vol.110 |
Number (no) | 76 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |