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.

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Outlines

· Motivation· Objectives· Methodology· Experiments· Conclusions· Comments

Intelligent Database Systems Lab

N.Y.U.S.T.

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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.

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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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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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Intelligent Database Systems Lab

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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