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Recommender Systems in E-Commerce

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Roger Chen
Roger Chen

This document summarizes recommender systems used in e-commerce and their benefits. It outlines examples of recommender systems from companies like Amazon, CDNOW, and eBay. It then categorizes recommender systems based on their interface (browsing, top-N lists, etc.) and recommendation technology (item-to-item correlation, people-to-people correlation, etc.). Finally, it discusses how recommender systems can enhance e-commerce by helping customers find products, suggesting additional purchases, and creating customer loyalty.

TechnologyBusiness
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Recommender Systems in E-Commerce J. Ben Schafer, Joseph Konstan, John Riedl E-COMMERCR 99,Denver,Colorado 1999 ACM Presentation by 邱信淵
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
Enhance E-commerce sales in 3 ways ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Recommender System Examples ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Recommender System Examples Amazon.com CDNOW eBay Levis Reel.com Moviefinder.com Customers who bought Album advisor Feedback profile Style finder Movie matches Match maker Eyes My CDNOW Movie map We predict Amazon.com delivers Book matcher Customer comments
Taxonomy of recommender systems --Interface ,[object Object],[object Object],[object Object],[object Object]
Taxonomy of recommender systems --Interface ,[object Object],[object Object],[object Object]
Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations Amazon.com Customers who Bought Similar Item Item to Item Correlation Purchase data Organic Navigation Eyes Email Attribute Based Keywords/freeform Amazon.com Delivers Email Attribute Based Selection options Book Matcher Top N List People to People Correlation Likert Request List Customer Comments Average Rating Text Comments Aggregated Rating Likert Text Organic Navigation
Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations CDNOW Album Advisor Similar Item Top N List Item to Item Correlation Purchase data Organic Navigation Keyword/freeform My CDNOW Top N List People to People Correlation Likert Organic Navigation Request List eBay Feedback Profile Average Rating Text Comments Aggregated Rating Likert Text Organic Navigation Levis Style Finder Top N List People to People Correlation Likert Request List
Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations Moviefinder.com Match Maker Similar Item Item to Item Correlation Editor’s choice Navigate to an item We Predict Top N List Ordered Search Results Average Rating People to People Correlation Aggregated Rating Likert Keywords/freeform Selection options Organic Navigation Reel.com Movie Matches Similar Item Item to Item Correlation Editor’s choice Organic Navigation Movie Map Browsing Attributed Based Editor’s choice Keywords/freeform
Taxonomy of recommender systems --Techniques ,[object Object],[object Object],[object Object]
Taxonomy of recommender systems --Techniques ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Finding Recommendations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
E-Commerce Opportunities Combine multiple types of data ( algorithms ) Buy-side  Sell-side Shared Information
Conclusion

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Recommender Systems in E-Commerce

  • 1. Recommender Systems in E-Commerce J. Ben Schafer, Joseph Konstan, John Riedl E-COMMERCR 99,Denver,Colorado 1999 ACM Presentation by 邱信淵
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  • 7. Recommender System Examples Amazon.com CDNOW eBay Levis Reel.com Moviefinder.com Customers who bought Album advisor Feedback profile Style finder Movie matches Match maker Eyes My CDNOW Movie map We predict Amazon.com delivers Book matcher Customer comments
  • 8.
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  • 10. Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations Amazon.com Customers who Bought Similar Item Item to Item Correlation Purchase data Organic Navigation Eyes Email Attribute Based Keywords/freeform Amazon.com Delivers Email Attribute Based Selection options Book Matcher Top N List People to People Correlation Likert Request List Customer Comments Average Rating Text Comments Aggregated Rating Likert Text Organic Navigation
  • 11. Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations CDNOW Album Advisor Similar Item Top N List Item to Item Correlation Purchase data Organic Navigation Keyword/freeform My CDNOW Top N List People to People Correlation Likert Organic Navigation Request List eBay Feedback Profile Average Rating Text Comments Aggregated Rating Likert Text Organic Navigation Levis Style Finder Top N List People to People Correlation Likert Request List
  • 12. Recommender System Examples Business/Application Recommendation Interface Recommendation Technology Finding Recommendations Moviefinder.com Match Maker Similar Item Item to Item Correlation Editor’s choice Navigate to an item We Predict Top N List Ordered Search Results Average Rating People to People Correlation Aggregated Rating Likert Keywords/freeform Selection options Organic Navigation Reel.com Movie Matches Similar Item Item to Item Correlation Editor’s choice Organic Navigation Movie Map Browsing Attributed Based Editor’s choice Keywords/freeform
  • 13.
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  • 17. E-Commerce Opportunities Combine multiple types of data ( algorithms ) Buy-side  Sell-side Shared Information