Citation

Yee, Hui Jia and Ting, Choo Yee and Ho, Chiung Ching (2018) Human elicited features in retail site analytics. In: 9th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing (IGRSM 2018), 24–25 April 2018,, Kuala Lumpur, Malaysia.

Text 39.pdf - Published Version Restricted to Repository staff only Download (686kB)

Abstract

Location selection is indispensable for a company or industry to survive for a long term. A strategically positioned retail location can increase the profitability and draw more customers for a company. Conventionally, a good location decision is associated with the relevant and significant location factors. However, integrating human subjective opinion as part of feature engineering process can be a challenge; there is no guarantee that these features can be optimum. In this light, this paper aims to investigate the impact of additional human elicitation features on the retail site selection model. This research focuses on retail site analytics to predict the sale of a telecommunication company in Malaysia. Apart from features such as geographical information, demographics and economics, this paper also includes the features determined by domain experts to investigate whether the human elicited features could improve the accuracy of sales estimation given a specific location. The findings of current work show that the additional of human elicited features successfully increase the model accuracy by 18.22%.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	retail trade/ site
Subjects:	H Social Sciences > HF Commerce > HF5001-6182 Business > HF5428-5429.6 Retail trade
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 Apr 2021 16:04
Last Modified:	04 Apr 2021 16:04
URII:	http://shdl.mmu.edu.my/id/eprint/7590

Downloads

Edit (login required)