Usage analytics: a process to extract and analyse usage data to understand user behaviour in cloud
Kesavulu, ManojORCID: 0000-0001-5505-9593, Dang-Nguyen, Duc-TienORCID: 0000-0002-2761-2213, Bezbradica, MarijaORCID: 0000-0001-9366-5113 and Helfert, MarkusORCID: 0000-0001-6546-6408
(2019)
Usage analytics: a process to extract and analyse usage data to understand user behaviour in cloud.
In: International Conference on Computer-Human Interaction Research and Applications(CHIRA 2017), 31 Oct– 2 Nov 2017, Funchal, Madeira, Portugal.
ISBN 978-3-030-32965-5
Usage in the software field deals with knowledge about how end-users use the application and how the application responds to the users’ action. Understanding usage data can help developers optimise the application development process by prioritising the resources such as time, cost and man power on features of the application which are critical for the user. However, in a complex cloud computing environment, the process of extracting and analysing usage data is difficult since the usage data is spread across various front-end interfaces and back-end underlying infrastructural components of the cloud that host the application and are of different types and formats. In this paper, we propose usage analytics, a process to extract and analyse usage to understand the behavioural usage patterns of the user with the aim to identify features critical to user. We demonstrate how to identify the features in a cloud based application, how to extract and analyse the usage data to understand the user behaviour.
Metadata
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Uncontrolled Keywords:
Human Behaviour Analysis; Usage data; Data extraction; Analytics · Application; Features; Cloud; User behaviour and usage pattern
CHIRA 2017: Computer-Human Interaction Research and Applications. Communications in Computer and Information Science (CCIS)
654.
Springer. ISBN 978-3-030-32965-5
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
Science Foundation Ireland grant 13/RC/2094, European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre
ID Code:
26847
Deposited On:
28 Mar 2022 12:17 by
Manoj Kesavulu
. Last Modified 09 May 2022 11:32