2021
DOI: 10.1016/j.asoc.2021.107677
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GPHC: A heuristic clustering method to customer segmentation

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Cited by 26 publications
(8 citation statements)
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“…The research could be expanded in the future to include derived clustering algorithms that improve segmentation performance while requiring fewer computational resources and taking less time. Furthermore, in the future, the segmentation can be implemented using the Stream Clustering algorithm, which tracks segments over time without costly recalculations and handles continuous streams of new observations without recompiling the entire model(s); GPHC, a heuristic clustering method to customer segmentation [53]; and a K-means clustering with an adaptive particle swarm optimization algorithm [54]. This research can also be improved with the Improved Augmented Regression Method [55].…”
Section: Discussionmentioning
confidence: 99%
“…The research could be expanded in the future to include derived clustering algorithms that improve segmentation performance while requiring fewer computational resources and taking less time. Furthermore, in the future, the segmentation can be implemented using the Stream Clustering algorithm, which tracks segments over time without costly recalculations and handles continuous streams of new observations without recompiling the entire model(s); GPHC, a heuristic clustering method to customer segmentation [53]; and a K-means clustering with an adaptive particle swarm optimization algorithm [54]. This research can also be improved with the Improved Augmented Regression Method [55].…”
Section: Discussionmentioning
confidence: 99%
“…They provide a holistic view of using AI to clustering algorithms implemented in the energy sector (Bogensperger & Fabel, 2021). Sun et al (2021) develop a heuristic clustering method for customer segmentation, termed Gaussian Peak Heuristic Clustering (GPHC) dealing with customer requirement data. They present a practical case to illustrate the effectiveness of GPHC in solving the customer segmentation problem.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Sivaguru et al [ 50 ] focused on dynamic customer segmentation through the use of modified dynamic fuzzy c-means clustering. Sun et al [ 51 ] developed a heuristic clustering method for customer segmentation. They used Gaussian peak heuristic-based clustering (GPHC) and a standardized Gaussian distribution to perform numerical experiments.…”
Section: Literature Reviewmentioning
confidence: 99%