Enterprise Intelligence, KDD 2016 workshop
San Francisco, CA, August 14, 2016
http://www.enterpriserelevance.com/kdd2016/

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Important Dates:
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Paper submissions: May 27, 2016
Notifications: June 13, 2016
Final submission: July 1, 2016
Workshop date: August 14, 2016

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Background:
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KDD techniques are at the core of enterprise intelligence systems in today’s data-driven and connected enterprises. Almost all components of the enterprise intelligence system, such as big data analytics and modeling, ROI attribution, decision support systems, cloud-based data security, privacy and compliance concerns, CRM, ATS, business intelligence, data exploration and visualization, are strongly influenced by the data mining discipline. In the past some of these areas have received isolated attention from KDD researchers, but we believe these areas deserve special attention from the KDD research community within the context of enterprise applications.

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Target audience:
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Industry practitioners of both enterprise and consumer applications, spanning ML applied researchers, data analytics and BI individual's, cloud-solution providers and customers e.g. CRM based intelligence amongst others Data Mining academicians working on novel machine learning algorithms, big data analytics and modeling, data exploration and visualization, and interested in enterprise applications Business school and MIS individuals working on Business analytics & Decision support systems.

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Topics of interest:
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Data mining and machine learning techniques related but not limited to:
- ROI estimation of enterprise products
- Privacy and Security for enterprise data
- Customer insights and CRM
- HR and Recruiting
- Marketing
- Forecasting and modeling challenges
- Retention and Churn prediction
- Enterprise level data preparation
- Supply chain management
- Enterprise level collaboration and sharing
- A/B testing and online experimentation

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Submission Details:
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Submission site: https://easychair.org/conferences/?conf=eikdd2016.
Authors are instructed to follow the ACM Proceedings Template. The paper length is limited to 10 pages, including tables, figures, references, and appendices. Each submitted paper will be evaluated by three PC members with respect to its novelty, significance, technical soundness, presentation, and experiments. Accepted papers will be published in EI-KDD'16 proceedings.

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Organizers:
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Abhishek Gupta, Head of Enterprise Intelligence@LinkedIn
George Karypis, Professor@University of Minnesota