Community-Based Service Ecosystem Evolution Analysis
- URL: http://arxiv.org/abs/2005.02729v1
- Date: Wed, 6 May 2020 11:00:04 GMT
- Title: Community-Based Service Ecosystem Evolution Analysis
- Authors: Mingyi Liu, Zhiying Tu, Xiaofei Xu, and Zhongjie Wang
- Abstract summary: Service ecosystem is a complex dynamic system with continuous evolution.
Existing studies on service ecosystem evolution are more about facilitating programmers to use services.
We present a method for analyzing service ecosystem evolution patterns from the perspective of the service community.
- Score: 4.770906657995415
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The prosperity of services and the frequent interaction between services
contribute to the formation of the service ecosystem. Service ecosystem is a
complex dynamic system with continuous evolution. Service providers voluntarily
or compulsorily participate in this evolutionary process and face great
opportunities and challenges. Existing studies on service ecosystem evolution
are more about facilitating programmers to use services and have achieved
remarkable results. However, the exploration of service ecosystem evolution
from the business level is still insufficient. To make up this deficiency, in
this paper, we present a method for analyzing service ecosystem evolution
patterns from the perspective of the service community. Firstly, we train a
service community evolution prediction model based on the community evolution
sequences. Secondly, we explain the prediction model, showing how different
factors affect the evolution of the service community. Finally, using the
interpretable predictions and prior knowledge, we present how to assist service
providers in making business decisions. Experiments on real-world data show
that this work can indeed provide business-level insights into service
ecosystem evolution. Additionally, all the data and well-documented code used
in this paper have been fully open source.
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