Skoči na glavni sadržaj

Izvorni znanstveni članak

https://doi.org/10.20532/cit.2018.1003863

Market Segmentation Analysis and Visualization Using K-Mode Clustering Algorithm for E-Commerce Business

Deepali Kamthania ; School of Information Technology, VIPS, GGSIP University, Delhi, India
Ashish Pawa ; School of Information Technology, VIPS, GGSIP University, Delhi, India
Srijit S. Madhavan ; School of Information Technology, VIPS, GGSIP University, Delhi, India


Puni tekst: engleski pdf 1.043 Kb

str. 57-68

preuzimanja: 3.945

citiraj


Sažetak


Today all business organizations are adopting data driven strategies to generate more revenue out of their business. Growing startups are investing a lot of money in data economy to maximize profits of business organizations by developing intelligent tools backed by machine learning and artificial intelligence. The nature of BI tool depends on factor like business goals, size, model, technology etc. In this paper architecture of business intelligence tool and decision process has been discussed with a focus on market segmentation, based on user behavior analysis using k-mode clustering algorithm and user geographical distributions. The proposed toolkit also incorporates interactive visualizations and maps.

Ključne riječi

clustering; market segmentation; data visualization; principal component analysis (PCA); k-mode

Hrčak ID:

203983

URI

https://hrcak.srce.hr/203983

Datum izdavanja:

6.7.2018.

Posjeta: 6.826 *