A data-driven evaluation framework for C2C online store quality

作者：Yang Sha; Li Shijun^*

来源：Journal of Computational Information Systems, 2015, 11(3): 927-934.

DOI：10.12733/jcis12999

• Cluster evaluations
• Data driven
• Evaluation framework
• Evaluation method
• Evaluation methods
• Explosive growth
• Online store
• Sorting algorithm

In the latest decade an explosive growth has been witnessed in C2C online stores. However, not all stores end up well for the sake of quality distinctions. With the results scored by domain experts in principle, the traditional evaluation methods are artificial and subjective. In this paper, we propose an improved cluster evaluation method based on data-driven to evaluate C2C online stores in speciality according to their crucial features. Furthermore, a sorting algorithm in the experiment is present to objectively score and rank the online stores selected from 8 significant categories on famous C2C platform TaoBao. The performance of our model is proved to be effective in the ultimate results.

• 出版日期2015