***** To join INSNA, visit http://www.insna.org ***** ================ CFP LSRS 2017 ============ 5th Workshop on Large Scale Recommender Systems co-located at ACM RecSys 2017 Lake Como, Italy https://lsrs2017.wordpress.com This workshop aims to foster discussions in several fields that are of interest to our growing community of recommendation system builders. On the practical side, we would like to encourage sharing of architecture and algorithm best practices in large-scale recommender systems as they are practiced in industry, as well as particular challenges and pain points. We hope this will guide future research that is system aware. On the research side, we focus on bringing in ideas and evaluations on scaling beyond the current generation of big data systems, with improved recommendation metrics. We believe the brightest minds from both sides will mutually benefit from the discussions and accelerate problem solving. Submission formats: =============== We invite submissions in two formats: extended abstracts (1-8 pages), or slides (15-20 slides). We encourage contributions in new theoretical research, practical solutions to particular aspects of scaling a recommender, best practices in scaling evaluation systems, and creative new applications of big data to large scale recommendation system. Important Dates: ============ Submission: June 22, 2017 Notification: July 29, 2017 Camera-ready version: August 18, 2017 Topics: ===== Our topics of interests include, but are not limited to: Data & Algorithms in Large-scale RS: ==================================== Scalable deep learning algorithm Big data processing in offline/near-line/online modules Data platforms for recommendation Large, unstructured and social data for recommendation Heterogeneous data fusion Sampling techniques Parallel algorithms Algorithm validation and correctness checking Systems of Large-scale RS: ========================== Architecture Programming Model Cloud platforms best for recommenders Real-time recommendation Online learning for recommendation Scalability and Robustness Evaluation of Large-scale RS: ========================== Comparison of algorithms’ application and effectiveness in different domains Offline optimization and online measurement consistency Evaluation metrics alignment with product/project goal Large user studies A/B testing methodology Organizers: ========= Tao Ye (Pandora Inc) Denis Parra (PUC Chile) Vito Ostuni (Pandora Inc) Tao Wang (Apple Inc) _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.