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Using the interest theory of rights and Hohfeldian taxonomy to address a gap in machine learning methods for legal document analysis

Computer Science

Using the interest theory of rights and Hohfeldian taxonomy to address a gap in machine learning methods for legal document analysis

A. Izzidien

This research conducted by Ahmed Izzidien explores the limitations of machine learning algorithms in legal document analysis, arguing that they fail to capture critical features like rights and duties. By incorporating the interest theory of rights and Hohfeldian taxonomy into stratified knowledge representation, it implements a groundbreaking heuristic that achieves a remarkable 92.5% accuracy in identifying essential relations within UK religious discrimination policy texts.

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