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list_of_projects [2015/11/03 15:20]
127.0.0.1 external edit
list_of_projects [2016/12/12 12:35]
patra
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 ======Recommender Projects ====== ======Recommender Projects ======
-=== Description===+=== Overview===
 The steady growth in the number of online users has led to the emergence of various online services such as Social Networks (Google+, Facebook, Twitter), e-commerce services (Movies: IMDB, Music: last.fm, Books: Goodreads). These online services leverage personalization schemes mostly Collaborative Filtering. Collaborative filtering schemes leverage profiles of other users to improve personalization quality. On the other hand, it opens up scalability and privacy issues. Additionally,​ recommenders also suffer from lack of explicit feedback (cold-start) from users. The steady growth in the number of online users has led to the emergence of various online services such as Social Networks (Google+, Facebook, Twitter), e-commerce services (Movies: IMDB, Music: last.fm, Books: Goodreads). These online services leverage personalization schemes mostly Collaborative Filtering. Collaborative filtering schemes leverage profiles of other users to improve personalization quality. On the other hand, it opens up scalability and privacy issues. Additionally,​ recommenders also suffer from lack of explicit feedback (cold-start) from users.
 === Scalable Recommender === === Scalable Recommender ===
 Scalability for recommenders stems from the fact that these services need to provide personalized recommendations to millions of customers in real-time. A project here for instance would consist in experimenting scalable solutions to recommend appropriate items to web users based on some collaborative filtering protocol.\\ Scalability for recommenders stems from the fact that these services need to provide personalized recommendations to millions of customers in real-time. A project here for instance would consist in experimenting scalable solutions to recommend appropriate items to web users based on some collaborative filtering protocol.\\
 Related papers:\\ Related papers:\\
-[1] __[[https://hal.inria.fr/hal-01080016/​document|HyRec: Leveraging Browsers for Scalable Recommenders]]__\\+[1] __[[http://dl.acm.org/citation.cfm?​id=2663315|HyRec: Leveraging Browsers for Scalable Recommenders]]__\\
 [2] __[[http://​research.microsoft.com/​pubs/​145190/​StreamRecDemo.pdf|StreamRec:​ A Real-Time Recommender System]]__ [2] __[[http://​research.microsoft.com/​pubs/​145190/​StreamRecDemo.pdf|StreamRec:​ A Real-Time Recommender System]]__
 === Privacy-preserving Recommender === === Privacy-preserving Recommender ===