Clustering data is the process of grouping items so that items in a group (cluster) are similar and items in different groups are dissimilar. After data has been clustered, the results can be analyzed ...

Arshia Naeem, Mariam Rehman, Maria Anjum, Muhammad Asif, Development of an efficient hierarchical clustering analysis using an agglomerative clustering algorithm, Current Science, Vol. 117, No. 6 (25 ...

In this paper, product usage data, employing a substitution-in-use criterion, are analyzed and shown to yield managerially useful product-market structures for financial services. These structures are ...

Clustering algorithms are a powerful form of AI that can be applied to business challenges from customer segmentation to fraud detection.

Then, several popular clustering techniques such as Agglomerative hierarchical clustering, K-means clustering algorithm, Partitioning around medoids, and Density-based clustering will be introduced.

Semantic keyword clustering can take your keyword research to the next level. Here's a Python script to help you do just that.