Eexcess blend-privacy-recommendation
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The EEXCESS project aims to provide privacy-respectful content recommendations to users. It includes a privacy plugin and privacy proxy to ensure user privacy policies are respected. The plugin provides transparency into what data is collected and how it is used, as well as user control over data disclosure and feedback on the benefits of disclosure. The proxy stores user profiles and activity while applying privacy settings, and only relays recommendation requests that comply with the user's privacy policy. The overall goal is to provide personalized recommendations while preserving user privacy through control and transparency of their personal data usage.
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Eexcess blend-privacy-recommendation
- 1. EEXCESS : Privacy-respectful content recommendation Benjamin Habegger, INSA Lyon
- 2. EEXCESS – Project Enhancing Europe’s eXchange in Cultural Educational and Scientific reSources. http://eexcess.eu/
- 4. EEXCESS – Main problem 4 Making existing qualilty content visible “Popular” long-tail content Long-tail content ≠ Quality content
- 5. EEXCESS - Objectives Content enrichment 5 Personalized recommendation Privacy preservation
- 6. EEXCESS – Simplified architecture Usage Mining EEXCESS Client Application Mendeley Search Econbiz Search Privacy Proxy EEXCESS Federated Recommender EEXCESS 6
- 7. Privacy Plugin – Recommendations 7
- 8. EEXCESS – Privacy objectives • Transparency – Show what personal data is being collected – Show how is this data used • Control & Feedback – Over which data is effectively being used – Granularity of disclosure – Show the user benefits of disclosure • Protection – Ensure user's policy is respected 8
- 9. Privacy Plugin – Profile edition 9
- 10. Privacy Plugin – Profile data collection 10 • Mendely auth + profile import
- 11. Privacy Proxy EEXCES S Privacy Plugin 11 Usage Mining EEXCES S Mendeley Search Econbiz Search Federated Recommender EEXCES S ● Receives recommendations ● User profile edits ● User browsing activity ● Recommendation requests Client Application ● Oauth interactions with Mendeley ● Recommendations ● Privacy settings ● Profile editing ● Privacy sandbox
- 12. Privacy Plugin - Transparency 12
- 13. Privacy Plugin – Trancparency 13
- 14. Privacy Plugin – Control & Feedback 14
- 15. Privacy Plugin – Control & Feedback 15
- 16. Privacy Proxy - Protection 16 Usage Mining EEXCES S Client Application Mendeley Search Econbiz Search Federated Recommender EEXCES S Privacy Proxy EEXCES S ● Receives recommendations ● Relays recommendations ● User profile edits ● User browsing activity ● Recommendation requests ● Stores profiles + browsing activity ● Applies privacy settings ● Relays policy-respectful recommendation requests
- 17. 17 Usage Mining EEXCES S Client Application Mendeley Search Econbiz Search Privacy Proxy EEXCES S ● Returns interleaved recommendations ● Searches Econbiz + Mendeley ● Receives recommendation requests Federated Recommender EEXCES S Basic Federated Recommender ● Receives recommendation request ● User static profile ● User recent activity ● Maps “user context” into a weighted term-based query
- 19. EEXCESS – Privacy challenges 19 D... Paul What is the average age ? 38 Paul is 2 years less than the average person in D External Knowledge 36
- 20. EEXCESS – Privacy challenges • Quality – Recommendations adapted to the user • Preserving privacy – Guaranteeing respect of privacy policy • Scalability – Ensuring the whole system scales • Quantifiable measures 20