摘要
以对象为基本检索单位的Web对象搜索技术正成为下一代智能搜索引擎的主要发展方向之一,而由于一些对象的部分属性具有时变性,高精度的时变对象辨识技术就成为实现高精度Web对象搜索的重要前提之一。从Web对象的不同属性具有对对象本质不同的表征能力、概率分布型属性值的演变大多服从某种分布以及确定型属性通常能比概率分布型属性更大程度地反映对象的区分度这些基本思想出发,提出了一种基于相似度计算的时变对象加权概率辨识模型。
Web object retrieval is becoming one of the main trends in the development of Intelligent Search Engines. High-precision time-varying objeets recognition technology is one of the important prerequisite for high-precision Web object retrieval. Usually, different attributes have different capabilities to token the essence of the object, stochastic attribute obeys some type of distribution, and determinate attribute has better separating capacity than stochastic attribute. In this paper, starting from the above-mentioned thought a weighted probabilistic model for identifying time varying objects was proposed to improve the accuracy of identify objects.
出处
《计算机科学》
CSCD
北大核心
2009年第9期246-247,273,共3页
Computer Science
基金
"日元贷款人才培养计划"(C01-P158)赴日访问学者项目资助
关键词
时变对象
辨识
相似度
确定型属性
概率分布型属性
Time-varying objects, Identification, Similarity, Determinate attribute, Stochastic attribute
