K-means clustering algorithm based on E-commerce big data

Abstract

As the technology improving, huge volumes of different types of data is being generated rapidly. Mining such data is a challenging task. One of the important tasks of mining is to group similar objects or similar data into cluster which is very much useful for analysis and prediction. K-means clustering method is a popular partition based approach for clustering data as it leads to good quality of results. This paper focuses on K-means clustering algorithm by analyzing the E-commerce big data. In this research, geographical location and unique identification number of the customer are considered as constraints for clustering.