Presentation 2010-06-14
Collaborative Filtering with A Bayesian Hierarchical Model
Hideki ASOH,
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
Date of Issue

Conference Information
Committee IBISML
Conference Date 2010/6/7(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Information-Based Induction Sciences and Machine Learning (IBISML)
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