Organized in conjunction with WSDM 2016 , the workshop aims to bring together interdisciplinary researchers from both academy and industry research labs, to share, exchange, learn, and develop upon preliminary results, novel concepts, ideas, principles, and methodologies on applying data mining and machine learning to Ad Targeting.
Recent advent of big data applications and platforms has led to a renaissance in many areas of machine learning and data mining. Computational advertising, a burgeoning field that accumulated revenue of over 20 billion dollars in the first half of 2014 in the US alone, has particularly benefited, and the industry has observed a steady two-digit growth in the past few years. However, in order to maintain and improve upon this positive trend, researchers in academia and industry alike are faced with numerous theoretical and practical challenges that require immediate attention.
Objective of the workshop is to bring together interdisciplinary practitioners and researchers from industrial and academic research labs to discuss state-of-the-art research and future directions in the fields of Ad Targeting, User Modeling, Recommender Systems, and related areas in the era of Big Data. We expect the workshop to help develop and grow stronger a community of interested researchers, and yield future collaborations and exchanges.
The topics of this workshop include, but are not limited to, the following areas:
| The workshop is organized by the following industry researchers:
The program committee of the workshop includes the following area experts:
| Important dates (midnight Hawaii time): Submission : Decisions : Camera-ready : Workshop : Formatting and publishing: There will be a 6-page limit on workshop papers using the ACM format. Please note that WSDM 2016 organizers will require at least one registration per published paper. |