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Newsletters An automatic news recommender system

Newsletters An automatic news recommender system

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Newsletters An automatic news recommender system

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  1. NewslettersAn automatic news recommender system Manish Agrawal March 12, 2008

  2. Motivation • Many data sources available online • Hard to keep track of all sources • Many sources might have similar content • Need to organize information by interest

  3. Crawler Meta Data (RDBMS) Register Community Clustering Indexer Query Index Date-wise Index Re-ranking based on feedback (if available) Newsletter DB Architecture Manish Agrawal, V.G.Vinod Vydiswaran and Kamal K. Gupta: “Automated generation of interest based newsletters”

  4. Clustering and re-ranking Crawling and Indexing Web Server FacebookAppl (GUI) Newsletter DB Newsletter Every day… Manish Agrawal, V.G.Vinod Vydiswaran and Kamal K. Gupta: “ Automated generation of interest based newsletters”

  5. Why Facebook? • Provides a great platform with in built social networks • Possible to make applications that deeply integrate into a user's Facebook experience. • FBML (Facebook Markup language) • FBJS (Facebook Javascript) • FQL (Facebook Query Language) • Facebook API

  6. Anatomy of a Facebook App (Integration Points) • Product directory • Left Navigation • Facebook Canvas Pages • Profile Box (Content cached on Facebook server) • Privacy settings • Mini-Feed • News-Feed • Alerts (E.g. Notification) • Requests (E.g. an invitation)

  7. Screen Snapshots (Canvas Page)

  8. Screen Snapshots (Profile Box)

  9. Screen Snapshots (Mini Feed)

  10. Future scope • More Personalization: Presently the newsletter is community specific. It can be personalized for individual Facebook user by exploiting user profiles and their friends’ profiles. • User feedback data (click-throughs, ratings, recommendations) can be used to improve the ranking algorithm and better model the community and the user

  11. Thank you!