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IABP 2016 - 2016 International Workshop on Intelligent Applications for Business Productivity (IABP 2016)

Date2016-09-07 - 2016-09-09

Deadline2016-04-15

VenueOstrava, Czech Republic Czech Republic

Keywords

Websitehttps://sites.google.com/site/iabpworkshop/home

Topics/Call fo Papers

Emergence of ICT paradigms has provided and enabled users with various avenues for facilitating their business activities. While on the one hand this has resulted in an increase in collaboration, on the other hand it has also increased the ways by which such collaborations can be achieved. However to ensure the main objective or aim of such business collaborations are achieved, it is important to develop applications that underpins the technology, platform and architecture of the such paradigms and utilize it in their domain. Given the importance of such applications, it is not surprising to see an upsurge of research activity in this area to develop applications by various businesses to achieve productivity.
The second International Workshop on Intelligent Applications for Business Productivity in conjunction with the 8th International Conference on Intelligent Networking and Collaborative Systems aims to provide a forum for world researchers to discuss their applications for enhancing Business productivity. The intention of the IABP 2016 is to bring together a community of researchers and practitioners who will provide a collection of work that is of utmost importance for achieving Business Productivity, reviewed by some of the experts and minds in the field.
Topics of interest:
Areas of focus and topics of special tracks for the workshop include one or more of the following (but are not limited to) themes:
? Semantic Web and Conceptual knowledge representation
? Linked data analytics
? Cyber Physical Systems (CPS)
? Managerial, operational and technological implications of Cloud Computing
? Application of Business Intelligence techniques in CPS and Cloud Computing
? Logistics Informatics
? Supply chain Informatics
? Asset Management in Big Logistics Data
? Asset Data Provenance

Last modified: 2016-01-17 18:58:04