Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11779/1906
Title: | Dog Walker Segmentation | Other Titles: | Köpek Gezdirici Segmentasyonu | Authors: | Ercan Alperen Karan Baris Çakar Tuna |
Keywords: | Clustering dog dog walkers GMM KMeans RFM Segmentation |
Publisher: | IEEE | Source: | Ercan, A., Karan, B., & Cakar, T. (2022). Köpek Gezdirici Segmentasyonu Dog Walker Segmentation. 2022 30th Signal Processing and Communications Applications Conference (SIU). https://doi.org/10.1109/siu55565.2022.986496 | Abstract: | In this study dog walkers were separated into clusters according to walkers' walk habits. Due to the fact that the distributions were non-normal, normalization algorithms were applied before the onset of clustering. After normalizing, K Means algorithm and Gaussian Mixture Models used for finding optimum cluster count. According to these clusters, walkers' consecutive months separated to follow-up their behavioral traits. This part of the study adds value to the project to examine walkers' behaviors closer. © 2022 IEEE. | URI: | https://hdl.handle.net/20.500.11779/1906 https://doi.org/10.1109/SIU55565.2022.9864967 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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File | Description | Size | Format | |
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Kpek_Gezdirici_Segmentasyonu_Dog_Walker_Segmentation.pdf | Full Text - Article | 931.92 kB | Adobe PDF | View/Open |
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