0 views collected around this technical thread.
This article explains the CRITIC (Criteria Importance Through Intercriteria Correlation) method, its step‑by‑step procedure, mathematical formulation, and a complete Python implementation that computes criterion weights for multi‑criteria decision making.
This article explains how to set the “best” reference in comprehensive evaluation models by introducing several modeling approaches—including full‑score, ideal‑object, TOPSIS, and DEA—along with the necessary terminology, weighting, and distance calculations.
The article presents three scatter algorithms—column scatter, weight distribution, and sliding‑window—that reorder recommendation lists to disperse similar items, describing their mechanics, computational complexities, experimental trade‑offs, and a hybrid case study for efficient, multi‑dimensional list diversification.