QMIQPN: An enhanced QPN based on qualitative mutual information for reducing ambiguity

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摘要

Enhanced Qualitative Probabilistic Network (QPN) is to make qualitative network more applicable by reducing ambiguity in a qualitative way. To reduce ambiguity in the basic QPN inference, we propose an enhanced QPN based on qualitative mutual information (QMI), named QMIQPN. Firstly, we give a strict definition of QMI. Secondly, based on the definition, we present the formalism of QMIQPN. Specifically, we take QMI as the strength of qualitative influence in QMIQPN, the qualitative influence with strength differs from the previous work, which additional expressiveness of the enhancement does not come at the expense of the property of symmetry of influence. Thirdly, we analyze several relative properties of qualitative influences with strengths. Furthermore, we improve the Sign-propagation Algorithm to reduce ambiguity and discuss its complexity. Finally, by experiments on several databases, we analyze the performance of QMIQPN. Theoretic analysis and experimental results illustrate that QMIQPN is qualitative and efficient, yet allows for reducing some ambiguities upon QPN inference.

论文关键词:Knowledge representation,Qualitative reasoning,Qualitative Probabilistic Networks,Qualitative mutual information,Ambiguity reduction

论文评审过程:Received 4 February 2013, Revised 1 June 2014, Accepted 23 July 2014, Available online 30 July 2014.

论文官网地址:https://doi.org/10.1016/j.knosys.2014.07.014