Measuring the quality of uncertain information using possibilistic logic

被引:0
|
作者
Hunter, A
Liu, WR
机构
[1] UCL, Dept Comp Sci, London WC1E 6BT, England
[2] Queens Univ Belfast, Sch Comp Sci, Belfast BT7 1NN, Antrim, North Ireland
关键词
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In previous papers, we have presented a framework for merging structured information in XML involving uncertainty in the form of probabilities, degrees of beliefs and necessity measures [HL04, HL05a, HL05b]. In this paper, we focus on the quality of uncertain information before merging. We first provide two definitions for measuring information quality of individually inconsistent possibilistic XML documents, and they complement the commonly used concept of inconsistency degree. These definitions enable us to identify if an XML document is of good or lower quality when it is inconsistent, as well as enable us to differentiate between documents that have the same degree of inconsistency. We then propose a more general method to measure the quality of an inconsistent possibilistic XML document in terms of a pair of coherence measures.
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收藏
页码:415 / 426
页数:12
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