南京大学学报(自然科学版) ›› 2023, Vol. 59 ›› Issue (4): 570579.doi: 10.13232/j.cnki.jnju.2023.04.004
摘要:
传统的偏好推理使用权衡增强的条件偏好网络(Tradeoff?Enhanced Conditional Preference Networks,TCP?nets)进行用户的偏好推理,不仅能高效地表示对元组的定性偏好关系并优化用户偏好结果,还能描述每个属性之间的偏好关系,其主要聚焦于关系元组中的单个属性的偏好.但把对条件偏好查询的技术推广到数据流的条件提取却是一个挑战,面临的技术困难主要是对数据流中序列的提取,对提取的序列进行占优查找等.首先,针对偏好数据流,提出一种时间条件查询语言Stream Pref来处理数据流;其次,在Stream Pref中加入时间索引来推理和规范数据流提取序列的时间条件偏好,提出提取对象序列算法、占优对象及占优序列查找算法和数据流序列间占优对比的算法;最后,在数据集上分析验证提出的算法的有效性.实验结果证明,提出的算法与min Top?k,Partition和Incpartition算法相比,得到的结果更准确.
中图分类号:
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