摘要
探讨了针对概率XML文档集中与内容相关的关键字检索结果的排序问题,针对概率XML文档的特征提出了一种新的排序模式.与仅取决于检索结果概率的检索排序算法不同,本文提出的排序算法充分考虑了节点对文档的区分程度、节点描述文档的程度,以及XML文档本身的结构特性,设计了满足以上特征的检索结果排序模型,并针对排序模型提出了新的倒排索引结构.新的排序算法可以快速完成关键字检索,并将最相关的信息提供给用户.模拟数据集实验验证了该方法的有效性.
Discusses the problem of efficiently ranking the search results of keyword related only to content on probabilistic XML data.A newranking model is presented according to the characteristic of probabilistic XML data.Unlike the existing ranking algorithms which only depend on the probabilities of retrieval results,the newranking algorithm proposed fully considered the degrees of nodes discriminating and describing the documents and the characteristic of probabilistic XML data.A ranking model of retrieval results which satisfied the above features is designed and a newinverted index structure for the ranking model is proposed.The newalgorithm can accomplish keyword search quickly,so as to provide the most relevant information to the users.The results of simulation experiment showthat the proposed method is effective.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2016年第8期1095-1099,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(6100024
61332006
U1401256)
国家重点基础研究计划项目(2011CB302200-G)
中央高校基本科研业务费专项资金资助项目(N130504006)
关键词
检索
概率XML数据
SLCA
排序
keyword search
probabilistic XML data
SLCA(smallest lowest common ancestor)
ranking