2nd International Workshop on Analytics for Service and Application Management
Izmir, Turkey, 02 November 2020
Co-located with CNSM 2020
With enterprise organizations generating petabytes of data each day, their use of, and reliance on data analytics to provide contextual insight into their operations is imperative for improving the implementation, management and delivery of services and applications. Approaches such as predictive data analytics, data mining, and machine learning are promising mechanisms to harness this immense stream of service and application data to meet the needs of an organization. The main goal of AnServApp is to present research and work-in-progress results in the area of data analytics, machine learning and cognitive science for service and application management.
Topics of interest include but are not limited to:
Authors are invited to submit original unpublished papers not under review elsewhere. Submissions will be subjected to a peer-review process. Regular papers should be submitted in IEEE 2-column format, not exceeding 6 pages. Authors should register and upload paper submissions https://edas.info/N27584
In addition to regular papers, short papers describing late-breaking advances and work-in-progress reports from ongoing research are also welcomed. These should also be in IEEE 2-column format between 2 to 4 pages in length.
Khurram Aziz, Dalhousie University, Canada
Pal Varga, Budapest University of Technology and Economics, Hungary
Paper Submission: September 21, 2020
Acceptance Notification: October 9, 2020
Camera Ready Submission: October 16, 2020
Workshop Date: November 02, 2020