基于路径内容索引相关关键节点的XML关键字查询算法  

XML keyword query algorithm based on path content index relevant keyword nodes

作　　者：姚全珠[1] 王丹[1] 蒋鹏飞[1] 

机构地区：[1]西安理工大学计算机科学与工程学院,西安710048

出　　处：《计算机应用》2016年第A01期210-212,216,共4页journal of Computer Applications

摘　　要：基于最小最低公共祖先和可扩展最低公共祖先主流查询语义的XML关键字查询方法中,路径内容索引方案减小了索引空间和降低了检索时间,但是其无法增加有效的信息来解决节点编码重复存储。针对路径内容索引方案所存在的问题,提出一种新的改进算法——路径内容索引相关关键节点(PCRK)算法。该算法利用路径内容索引方案可以减少索引空间和时间的优点,并结合相关关键字节点能够获得准确的查询结果并且能去除冗余节点的特性,从而克服路径内容索引方案在节点编码重复存储上存在的缺陷。实验结果表明该算法在减少索引空间的同时也缩短了查询时间,并且提高了查询结果的准确性。Based on Smallest Lowest Common Ancestor（ SLCA） and Exclusive Lowest Common Ancestor（ ELCA）mainstream query methods for XML keywords of query semantics,path content index reduces index space and retrieval time,but it can＇ t increase the effective information to solve repeated storage nodes coding.An improved algorithm named as the Path Content index Relevant Keyword node（ PCRK） algorithm was proposed for the existing problem of path content index.Path content index has advantages to reduce index space and retrieval time,relevant keyword nodes were used to obtain accurate query results and remove redundant nodes,it can solve path content index flaws exists were used in node coding on repeat storage.Simulation experimental results show that this algorithm can not only shorten the query time as well as reduce the size of the index space,but also improve the accuracy of the query results.

关 键 词：可扩展标记语言 关键字查询 最小最低公共祖先 可扩展最低公共祖先 相关关键字节点 

分 类 号：TP311.131[自动化与计算机技术—计算机软件与理论]