Tutorials at ACM RecSys 2013
Learning to Rank
Beyond Friendship: The Art, Science and Applications of Recommending People to People in Social Networks
by Luiz Augusto Pizzato (University of Sydney, Australia)
& Anmol Bhasin (LinkedIn, USA)
While Recommender Systems are powerful drivers of engagement and transactional utility in social networks, People recommenders are a fairly involved and diverse subdomain. Consider that movies are recommended to be watched, news is recommended to be read, people however, are recommended for a plethora of reasons – such as recommendation of people to befriend, follow, partner, targets for an advertisement or service, recruiting, partnering romantically and to join thematic interest groups.
This tutorial aims to first describe the problem domain, touch upon classical approaches like link analysis and collaborative filtering and then take a rapid deep dive into the unique aspects of this problem space like Reciprocity, Intent understanding of recommender and the recomendee, Contextual people recommendations in communication flows and Social Referrals – a paradigm for delivery of recommendations using the Social Graph. These aspects will be discussed in the context of published original work developed by the authors and their collaborators and in many cases deployed in massive-scale real world applications on professional networks such as LinkedIn.
The basics of Social Recommenders
People recommender systems
Special Topics in People Recommenders
Why reciprocal (people) recommenders are different to traditional (product) recommendations
The pre-requisite for this tutorial is some familiarity with foundational Recommender Systems, Data Mining, Machine Learning and Social Network Analysis literature.
Oct 13, 2013 (08:30 – 10:15)