The paper merges numerical and textual similarities in spectral clustering with a weight tuned on approved/rejected loan labels, yet the resulting 'recruitment implies lower risk' finding is contaminated by that same label information.
Recent advances have focused on calculating similarity matrix for heterogeneous data clustering (Gupta, Thakar, & Tokekar, 2025 )
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Advanced spectral clustering for heterogeneous data in credit risk monitoring systems
The paper merges numerical and textual similarities in spectral clustering with a weight tuned on approved/rejected loan labels, yet the resulting 'recruitment implies lower risk' finding is contaminated by that same label information.