utilizing marginal net utility for recommendation in e-commerce
DESCRIPTION
Utilizing Marginal Net Utility for Recommendation in E-commerce. Author : Jian Wang, Yi Zhang Presented : Fen-Rou Ciou ACM, 2011. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation. To better match users’ purchase decision in the real world. - PowerPoint PPT PresentationTRANSCRIPT
Intelligent Database Systems Lab
國立雲林科技大學National Yunlin University of Science and Technology
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Utilizing Marginal Net Utility for Recommendation in E-commerce
Author : Jian Wang, Yi Zhang
Presented : Fen-Rou Ciou
ACM, 2011
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.
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Outlines
· Motivation· Objectives· Methodology· Experiments· Conclusions· Comments
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.
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Motivation
· To better match users’ purchase decision in the real world.
· Most of existing recommendation algorithms has three disadvantages.─ Marginal net utility optimization ─ Cannot model the above two different products well. ─ Highest predicted ratings to recommend.
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.
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Objectives
· This paper use marginal net utility to develop recommendation algorithms.
· The new function contains a factor to control the product’s marginal utility diminishing rate.
Marginal net utility
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
New marginal utility function
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
New marginal net utility function
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Methodology
Apply new marginal utility function on SVD
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Intelligent Database Systems Lab
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I. M.Experiments
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Experiments
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Intelligent Database Systems Lab
N.Y.U.S.T.
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Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.Experiments
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Intelligent Database Systems Lab
N.Y.U.S.T.
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Conclusions
· On shop.com data, the new methods perform significantly better than baselines.
· performs better in the re-purchase product recommendation task.
· is more useful in recommending new products
Intelligent Database Systems Lab
N.Y.U.S.T.
I. M.
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Comments
· Advantages─ .
· Applications─ Recommender System, Consumer Utility Function