AI-POWERED METADATA INTELLIGENCE: CLUSTERING FINANCIAL REPORTS FOR DYNAMIC DISCOVERY
DOI:
https://doi.org/10.34218/IJCET_15_04_085Keywords:
Metadata Intelligence, Report Clustering, Financial Reporting, Machine Learning, Unsupervised Learning, NLP, Report Discovery, AI In BI, Enterprise SearchAbstract
As enterprises grapple with vast volumes of financial data and report artifacts, finding relevant reports in legacy and cloud-based business intelligence systems becomes increasingly complex. This article explores how machine learning (ML) can be used to enable intelligent metadata classification and clustering of financial reports to support dynamic, user-centric discovery. By applying natural language processing (NLP), unsupervised learning algorithms, and user interaction analytics, organizations can shift from static folder-based hierarchies to adaptive, recommendation-driven interfaces that improve efficiency, security, and decision-making.
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Copyright (c) 2024 Preeta Pillai (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
