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================ CFP LSRS 2106 ============
4th Workshop on Large Scale Recommender Systems
co-located at ACM RecSys 2016
Boston, MA, USA

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: 2016-06-24
Notification: 2016-08-03
Workshop date: 2016-09-16

Our topics of interests include, but are not limited to:

Systems of Large-scale RS:
Programming Model
Cloud platforms best for recommenders
Real-time recommendation
Online learning for recommendation
Scalability and Robustness

Data & Algorithms in Large-scale RS:
Big data processing in offline/near-line/online modules
Streaming data for recommendation
Data platforms for recommendation
Large, unstructured and social data for recommendation
Heterogeneous data fusion
Sampling techniques
Parallel algorithms
Incremental algorithms
Algorithm validation and correctness checking

Evaluation of Large-scale RS:
Offline optimization and online measurement consistency
Evaluation metrics alignment with product/project goal
Large data and privacy issue
Large user studies

Tao Ye, [log in to unmask], Pandora Inc.
Danny Bickson, [log in to unmask], Dato Inc.
Denis Parra, [log in to unmask], PUC Chile

Denis Parra
Escuela de Ingenieria

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