Ambiguity reduction based on qualitative mutual information in qualitative probabilistic networks

作者：Lü Ya Li; Liao Shi Zhong^*

来源：Pattem Recognition and Aitificial Intelligence, 2011, 24(1): 123-129.

• Inference ambiguity
• Mutual informations
• Parallel composition
• Propagation algorithm
• Qualitative influence
• Qualitative influences
• Qualitative mutual information
• Qualitative probabilistic networks
• Theoretic analysis

To reduce the inference ambiguity in the sign-propagation algorithm, a method is proposed based on qualitative mutual information in qualitative probabilistic networks (QPN). Firstly, the definition of qualitative mutual information is given. Then, an enhanced formalism of qualitative probabilistic networks (EQPN) is presented based on this definition, which can distinguish between strong and weak influences. Thirdly, symmetry, transitivity and parallel composition of qualitative influences in EQPN are analyzed. Finally, the correctness and efficiency of the sign-propagation algorithm in EQPN are verified by experiments on the Antibiotics database. Theoretic analysis and experimental results show that EQPN is qualitative, efficient, and it reduces inference ambiguity correctly.

• 出版日期2011
• 单位天津大学