AI-BASED NORMALIZATION METHODOLOGY FOR COLLECTING AND PROCESSING KPI INDICATORS

Shuhratov , Mamurjon

Innovation science and technologiy · 2025-yil

Annotatsiya

The heterogeneity of employee performance data collected in organizations—stemming from variations informat, structure, and recording methods—creates significant inaccuracies within KPI systems. This article proposesan AI-based normalization methodology aimed at standardizing KPI data, automatically filtering noisy and inconsistententries, and converting heterogeneous inputs into a unified mathematical representation. The study employs NLPtechniques, min–max scaling, z-score standardization, Isolation Forest, and sentence-embedding models. Experimentalresults demonstrate that the proposed normalization pipeline increases data accuracy from 78% to 94% and reduces theKPI calculation time from 40 hours to 0.8 hours

Maqola ma’lumotlari
MualliflarShuhratov , Mamurjon
JurnalInnovation science and technologiy
Nashr sanasi2025-12-01
Jild1
Son12
TilIngliz
DOI10.5281/zenodo.17847027

Kalit so‘zlar

normalization, artificial intelligence, data cleaning, automation, NLP.

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