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: | RFM Dog Walkers Dog GMM KMeans Segmentation Clustering |
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 |
Series/Report no.: | Signal Processing and Communications Applications Conference |
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. |
URI: | https://doi.org/10.1109/SIU55565.2022.9864967 |
ISBN: | 9781665450928 |
ISSN: | 2165-0608 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Files in This Item:
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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