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- W2892987128 abstract "Location analytics has been employed to capture insights about business, retail, disaster planning, public safety, conservation of energy, and many more. Despite the success of location analytics in various domains, obtaining a set of optimal features or criteria for analysis purposes remained a challenge. Hence, feature selection plays an important role in obtaining the optimal features as it determines the valuable and significant factors to be included in the final analytical dataset. In this light, feature selection was proposed to optimize the geospatial features to predict sales as well as recommendation for locations when establishing new outlets. In this study, sales data for a certain telecommunication company was used. This paper ends with the results of empirical experiments and recommendation of location characteristics that optimize yearly sales." @default.
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- W2892987128 date "2018-01-01" @default.
- W2892987128 modified "2023-09-23" @default.
- W2892987128 title "Optimal geospatial features for sales analytics" @default.
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- W2892987128 doi "https://doi.org/10.1063/1.5055554" @default.
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