Open Internet by MindsNet

Semantics in Tabular Data Clustering

Traditional clustering methods, such as K-Means and one-hot encoding, fail to capture semantic relationships between categorical data, leading to inaccurate clustering results. This limitation is particularly problematic in domains where categories have different meanings and implications. For instance, 'Sales Representative' and 'Research Scientist' are treated as equally distant from 'Sales Manager' despite their distinct roles. This challenge affects various applications, including HR analytics and customer segmentation.

Computing & Technology, Computer Science, Machine Learning