A Diversity-based Method for Infrequent Purchase Decision

Support in E-Commerce

Author： Rustam Vahidov , Fei Ji Source： Electrnic Commerce Research and Applications Vol.4, 2005, pp. 143-158Presented By： Ya-Ju Liu ( 劉雅茹 )Date： 2005/12/15

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Outline

Introduction Methodology

• Fuzzy Weighted-Sum Model

• Cluster Analysis

Architecture Conclusion Comment

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Introduction

Motivation• The wealth of information threatens to overload the

customers

Purpose• Propose a method for supporting consumer buying

decisions in EC

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Methodology

Fuzzy weighted-sum model (FWSM)• Partition the alternatives into different grade

Cluster analysis (CA)• Explore similarity between people, products, and behaviors

• Provide the most dissimilar cluster

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FWSM

： Fuzzy utility

： Utility of the ith attribute of product

： Fuzzy weight of that attribute

Calculate the attractiveness of product

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CA Group observations based on the similarity measure

• X, Y ： products

• wi ： weight

• i ： product features

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Architecture

User Interface(WWW)

CriteriaManagement

Fuzzy FilterProduct DB

Clustering Module

Recommendations Generator

Recommendations Profiles

Buyer

Client

Server

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Criteria Management

Partition the products into different classes• Fuzzy terms Fuzzy weights

Provide the most dissimilar clusters• Cluster analysis (CA)

• Euclidian distance metric

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Fuzzy Weight

567

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Fuzzy Filter

Assign grades to the products• Fuzzy utility

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Fuzzy Utility (1/2)

0.75*1+0.714*1+0.429*1+0.461*1+1*1+1*1+0*1+0*1+0.679*1 = 5.05

0.75*4+0.714*4+0.429*4+0.461*4+1*4+1*4+0*4+0*4+0.679*4 = 20.21

0.75*7+0.714*7+0.429*7+0.461*7+1*7+1*7+0*7+0*7+0.679*7 = 35.36

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Fuzzy Utility (2/2)

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Clustering Module

Clustered using hierarchical method N diverse alternatives are presented to the user

• Example ：• According to the weights (price)

• N=3

• Three alternatives would greatly vary on price and be presented

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Recommender Profile

Generated by the system in terms of key types Match between the alternatives and the profiles

LuxuryValueBudget

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Recommendation List

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Conclusion

Fuzzy model• Allow customers some level of latitude in describing their

preferences

Diverse product recommendations would help the customers to find the right products

The method has to be effectively employed by the EC websites

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Comment

Fuzzy method using in recommender system• Crisp Set Fuzzy Set

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Thanks for your listening