[ACM Press the 4th Workshop - Salzburg, Austria (2011.04.10-2011.04.13)] Proceedings of the 4th Workshop on Social Network Systems - SNS '11 - A recommendation system for spots in location-based online social networks

[ACM Press the 4th Workshop - Salzburg,

[ACM Press the 4th Workshop - Salzburg, Austria (2011.04.10-2011.04.13)] Proceedings of the 4th Workshop on Social Network Systems - SNS '11 - Facebook immune system

✍ Stein, Tao; Chen, Erdong; Mangla, Karan 📂 Article 📅 2011 🏛 ACM Press ⚖ 254 KB

[ACM Press the 4th Workshop - Amsterdam,

[ACM Press the 4th Workshop - Amsterdam, The Netherlands (2014.04.13-2014.04.13)] Proceedings of the 4th Workshop on Context-Awareness in Retrieval and Recommendation - CARR '14 - A context-aware retrieval system for mobile applications

✍ Mizzaro, Stefano; Pavan, Marco; Scagnetto, Ivan; Zanello, Ivano 📂 Article 📅 2014 🏛 ACM Press ⚖ 593 KB

[ACM Press the 18th SIGSPATIAL Internati

[ACM Press the 18th SIGSPATIAL International Conference - San Jose, California (2010.11.02-2010.11.05)] Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '10 - Location recommendation for location-based social networks

✍ Ye, Mao; Yin, Peifeng; Lee, Wang-Chien 📂 Article 📅 2010 🏛 ACM Press ⚖ 568 KB

[ACM Press the 34th international ACM SI

[ACM Press the 34th international ACM SIGIR conference - Beijing, China (2011.07.24-2011.07.28)] Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11 - A large scale machine learning system for recommending heterogeneous content in social networks

✍ Shi, Yanxin; Ye, David; Goder, Andrey; Narayanan, Srinivas 📂 Article 📅 2011 🏛 ACM Press ⚖ 356 KB

[ACM Press the 34th international ACM SI

[ACM Press the 34th international ACM SIGIR conference - Beijing, China (2011.07.24-2011.07.28)] Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11 - A large scale machine learning system for recommending heterogeneous content in social networks

✍ Shi, Yanxin; Ye, David; Goder, Andrey; Narayanan, Srinivas 📂 Article 📅 2011 🏛 ACM Press ⚖ 356 KB

The goal of the Facebook recommendation engine is to compare and rank heterogeneous types of content in order to find the most relevant recommendations based on user preference and page context. The challenges for such a recommendation engine include several aspects: 1) the online queries being proc