<ul><li>This article introduces a preference collaborative measure framework based on an updated belief system.</li><li>The framework aims to reduce human intervention and improve the accuracy and efficiency of preference measures.</li><li>It proposes algorithms to discover common preferences, update the belief system, and classify preference rules.</li><li>Experimental results show that the proposed algorithms outperform state-of-the-art algorithms in most aspects.</li></ul>

Contextual Preference Collaborative Measure Framework Based on Belief System

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