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Recommender Systems
A sub-topic of eCommerce, recommender systems analyse user behaviour based on past purchases and recommend purchases customised to users’ perceived tastes.
Related Publications:
- [WebSci2009] Karpf, David - Why Bowl Alone When You Can Flashmob the Bowling Alley?: Implications of the Mobile Web for Online-Offline Reputation Systems.
- [WebSci2009] Victor, Patricia, Cornelis, Chris, De Cock, Martine, Teredesai, Ankur - Trust- and Distrust-Based Recommendations for Controversial Reviews
- [WebSci2017] Larissa Spinelli, Mark Crovella - Closed-Loop Opinion Formation
- [WebSci2017] Frederick Ayala-Gómez, Bálint Daróczy, Michael Mathioudakis, András Benczúr, Aristides Gionis - Where Could We Go?: Recommendations for Groups in Location-Based Social Networks
- [WebSci2017] Qing Ke - Sharing Means Renting?: An Entire-marketplace Analysis of Airbnb
- [WebSci2017] Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, Michael Mathioudakis - Factors in Recommending Contrarian Content on Social Media
- [WebSci2010] Chandrasekar, Raman, Jain, Kamal - Peer-to-Peer Human Computation & “Help Me Decide”: Enabling search users to help other users make purchase decisions.
- [WebSci2011] Fabian Abel, Qi Gao, Geert-Jan Houben, Ke Tao - Analyzing Temporal Dynamics in Twitter Profiles for Personalized Recommendations in the Social Web.