Approaches to Clustering in Customer Segmentation

Tripathi, Shreya; Bhardwaj, Aditya; Poovammal, E.

doi:10.14419/ijet.v7i3.12.16505

Cited by 43 publications

(15 citation statements)

References 30 publications

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“…6. The number of clusters given by these methods confirms the rule of thumb that suggests that the number of clusters should not be few or many to tailor marketing strategy and optimize resources [19]. It also makes sense in the eyes of the researchers to have optimum clusters of less than five in the banking industry.…”

Section: B Data Description and Processingsupporting

confidence: 61%

Using Unsupervised Machine Learning Techniques for Behavioral-based Credit Card Users Segmentation in Africa

et al. 2020

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Section: B Data Description and Processingsupporting

confidence: 61%

Using Unsupervised Machine Learning Techniques for Behavioral-based Credit Card Users Segmentation in Africa

et al. 2020

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“…It should be noted that in the case of contextual advertising, marketers have a fairly extensive array of information that characterizes the behavioral activity of product users. Therefore, the second approach to calculating the lift coefficient is to use cluster analysis [16,17] to construct the Lorentz curve. In order to assess the uniformity of user interest in an ad, as well as to compare ads with their interests, it is necessary to proceed to cluster analysis of user reaction to ads [18].…”

Section: Methodsmentioning

confidence: 99%

“…However, in the case of an ad campaign, this selection may change dynamically. Therefore, hierarchical clustering methods are used as the most appropriate method [17], which do not require a training sample and allow for dividing clients into groups based on characteristics.…”

Section: Mathematical Methods and Algorithms Of Business Informaticsmentioning

confidence: 99%

Structuring advertising campaign costs considering the asymmetry of users’ interests

Kislyakov¹

2020

Bus. Inform.

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This work is devoted to the highly topical problem of structuring costs for contextual and targeted advertising on the Internet. The choice of the ad campaign financing structure is considered from the point of view of violating the principle of symmetry of user interest in ads. The purpose of this work is to develop a methodology for structuring advertising campaign costs based on cluster analysis, taking into account the asymmetry of user interest in advertising. The key feature of the research is the description of the possibility of using the asymmetry of user interest in application solutions, such as online advertising. The Gini coefficient is used as an indicator of the degree of imbalance in the manifestation of a feature in clustering, and the features of using the lift coefficient and the Lorentz curve to evaluate the effectiveness of contextual and targeted advertising for various groups of customers are also considered. Using the Gini index and cluster analysis, you can analyze the possibilities of increasing ad revenue and compare it with the absence of any policy for structuring advertising costs. Identifying such patterns in consumer groups allows you to identify the main directions of product development and customer interest in it. The method described here should be used to improve the effectiveness of banner advertising and clustering algorithms. This approach does not improve banner clickability, but allows you to implement an individual approach to advertising products with the current number of clicks and more effectively structure the cost of various types of advertising.

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“…Then, the WSS according to the number of clusters were plotted as curves, as shown in Figure 5. The location of a bend in the graph is generally regarded as an indicator of the number of appropriate clusters [35]. When the bending point was not visible obviously, the largest distance of a line that is perpendicular from a straight line drawn between the point of the first cluster and the last cluster indicated the optimal number of clusters.…”

Section: Application Of Morphometric Data To Analyze the Knee Prostheses For Thaismentioning

confidence: 99%

Morphometric Analysis and Three-Dimensional Computed Tomography Reconstruction of Thai Distal Femur

2021

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This study evaluates the distal femur morphology of the Thai population using a three-dimensional (3D) measurement method, measuring the distance between the triangular point of the femoral 3D model. The 3D model of 360 Thai femoral obtained from 180 volunteers (90 males, 90 females; range 20–50 years, average 32.8 years) was created using reverse engineering techniques from computed tomography imaging data. Using the 3D identified landmark method, the morphometric parameters evaluated included transepicondylar axis length (TEA), mediolateral length (ML), anteroposterior width (AP), medial anteroposterior width (MAP), lateral anteroposterior width (LAP), medial condyle width (MCW), lateral condyle width (LCW), intercondylar notch width (WIN), intercondylar notch depth (DIN), medial posterior condyle height (MPC), lateral posterior condyle height (LPC), femoral aspect ratio (ML/AP), lateral femoral aspect ratio (ML/LAP), and medial femoral aspect ratio (ML/MAP). The measured data were summarized for the analysis of an average value and standard deviation. Statistical analysis was performed using the independent samples t-test, unequal variances t-test, and linear regression. A p-value less than 0.05 (<0.05) was regarded as statistically significant and indicates strong evidence of the hypothesis. Additionally, the K-means clustering analysis of Thai distal femoral to the optimum size of the prosthesis with the correlation between ML length and AP width was performed. The results found that the morphometric parameters of the Thai male distal femur were significantly different and higher than those of Thai females, except for the ratio of ML/AP and ML/MAP. Comparatively, there was a significant difference between the specific size of Thai distal femur and that of the Korean population, which was also smaller than that for Caucasians. In addition, there was a mismatch between the distal femoral component sizing of knee prosthesis and what is available and commonly used in Thailand. At least six sizes of ML and/or AP should be recommended for the reasonable design of distal femoral prosthesis for covering the anatomy of Thais. These data are useful for predicting the morphometric parameters in forensic anthropology and provide basic data for the design of knee prostheses suitable for the Thai population.

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Approaches to Clustering in Customer Segmentation

Cited by 43 publications

References 30 publications

Using Unsupervised Machine Learning Techniques for Behavioral-based Credit Card Users Segmentation in Africa

Using Unsupervised Machine Learning Techniques for Behavioral-based Credit Card Users Segmentation in Africa

Structuring advertising campaign costs considering the asymmetry of users’ interests

Morphometric Analysis and Three-Dimensional Computed Tomography Reconstruction of Thai Distal Femur

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