[1]赵艳妮[][],郭华磊[],马军生[]. 基于路径权重的XML文档相似度仿真研究[J].计算机技术与发展,2016,26(09):197-200.
　ZHAO Yan-ni[][],GUO Hua-lei[],MA Jun-sheng[]. Simulation Research of XML Document Similarity Based on Path Weighting[J].,2016,26(09):197-200.
点击复制

 基于路径权重的XML文档相似度仿真研究()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年09期
页码:
197-200
栏目:
智能、算法、系统工程
出版日期:
2016-09-10

文章信息/Info

Title:
 Simulation Research of XML Document Similarity Based on Path Weighting
文章编号:
1673-629X（2016)09-0197-04
作者:
赵艳妮[1][2];  郭华磊[3]; 马军生[3]
1.陕西职业技术学院 计算机科学系；2.西安理工大学 自动化与信息工程学院；3.西安通信学院 信息服务系
Author(s):
 ZHAO Yan-ni[1][2]; GUO Hua-lei[3]; MA Jun-sheng[2]
关键词:
 ; 相似度; 路径权重; 查询树; 文档树
Keywords:
 ; similarity; path weight ; query tree; document tree
分类号:
TP391.9
文献标志码:
A
摘要:
 针对XML文档查询效率低和准确度不理想的问题，提出一种基于路径权重的树相似度算法。该算法以树节点信息相似度和树结构相似度为出发点，依据信息组织主次分明的客观规律，信息按照重要程度依次排列在树的各个层次，树节点信息自上至下重要程度逐渐减弱。根据距离根节点越近的节点表示的信息越重要，最低层信息的重要性最小的特点，依照树节点在XML文档树中的层次自动计算该节点的路径权重，克服了传统XML文档树相似度计算中树节点信息权重平均分配或手工设置的缺点，解决了XML文档树的相似度自动计算问题，实现了XML查询树与文档树的快速匹配。仿真结果表明，该算法在大量XML文档检索方面查询效率、查准率和查全率都得到有效改进。
Abstract:
 In order to realize the rapid and accurate retrieval of the XML document information,a tree similarity algorithm based on path weight is proposed. It considers the tree node information similarity and structural similarity,and the information is arranged in each level of the tree in accordance with the degree of importance by object rules of primary and secondary information organization,making the de-gree of importance for tree node information weakened from up to down. According to the characteristics that the node with closer dis-tance from the root node represents the more important information,and the lowest level of the information has minimal importance,the path weight is calculated automatically in accordance with the tree node in XML document tree level,which overcomes the disadvantage of equally distribution or manual setting for tree node information weigh in the traditional XML document,and solves the similarity calcu-lation of XML document tree,and realizes the fast matching of XML query tree and document. Simulation shows that the algorithm is im-proved in query efficiency,precision and recall.

相似文献/References:

[1]曹道友 程家兴.基于改进的选择算子和交叉算子的遗传算法[J].计算机技术与发展,2010,(02):44.
　CAO Dao-you,CHENG Jia-xing.A Genetic Algorithm Based on Modified Selection Operator and Crossover Operator[J].,2010,(09):44.
[2]王春雪 王继成 郑吉.谱聚类在图像检索中的应用[J].计算机技术与发展,2009,(01):207.
　WANG Chun-xue,WANG Ji-cheng,ZHENG Ji.Application of Spectral Clustering in Image Retrieval[J].,2009,(09):207.
[3]林智超 朱国进.一种基于FCA的概念相似度算法[J].计算机技术与发展,2008,(09):112.
　LIN Zhi-ehao,ZHU Guo-jin.A Concept Similarity Algorithm Based on FCA[J].,2008,(09):112.
[4]乌庆敏 杨思春.基于潜在语义分析的智能答疑系统研究与实现[J].计算机技术与发展,2008,(09):251.
　WU Qing-min,YANG Si-chun.Research on Intelligent Question Answering System Based on Latent Semantic Analysis[J].,2008,(09):251.
[5]盛步云 万哲 丁毓峰.BPMS中一种基于流程异常库的异常处理方法[J].计算机技术与发展,2008,(12):84.
　SHENG Bu-yun,WAN Zhe,DING Yu-feng.A Method Based on Process Abnormity Set for Resolving Abnormity in BPMS[J].,2008,(09):84.
[6]程舒通.Web点击流的频繁模式聚类算法[J].计算机技术与发展,2007,(09):18.
　CHENG Shu-tong.Clustering Algorithm of Web Click Flow Frequency Pattern[J].,2007,(09):18.
[7]闫蓉 张蕾.一种新的汉语词义消歧方法[J].计算机技术与发展,2006,(03):22.
　YAN Rong,ZHANG Lei.New Chinese Word Sense Disambiguation Method[J].,2006,(09):22.
[8]李泽军 曾利军 刘文华.基于相关性和语义相似度融合的查询扩展方法[J].计算机技术与发展,2010,(09):66.
　LI Ze-jun,ZENG Li-jun,LIU Wen-hua.Query Expansion Method Based on Relativity and Similarity Inosculate[J].,2010,(09):66.
[9]李文娟 胡春生.基于聚类优化覆盖的集成学习方法[J].计算机技术与发展,2010,(11):51.
　LI Wen-juan,HU Chun-sheng.A Combined Learning Algorithm of Optimum Covering Based on Clustering[J].,2010,(09):51.
[10]贾晓倩 刘方爱.基于最近邻搜索算法分组式P2P网络拓扑模型[J].计算机技术与发展,2010,(11):100.
　JIA Xiao-qian,LIU Fang-ai.A Topology Model Based on Nearest Neighbor for P2P Group Networks[J].,2010,(09):100.
[11]高国强,黄吕威,陈丰钰. 使用网络搜索引擎计算汉语词汇的语义相似度[J].计算机技术与发展,2014,24(07):84.
　GAO Guo-qiang,HUANG Lü-wei CHEN Feng-yu. Calculation of Chinese Words Semantic Similarity Using Network Search Engines[J].,2014,24(09):84.
[12]卢传耀,徐敏. 基于加权的冗余相似本体实例发现的研究[J].计算机技术与发展,2014,24(09):11.
　LU Chuan-yao,XU Min. Research on Ontology Instances Found Redundancy Based on Entropy Weighted[J].,2014,24(09):11.
[13]李振博,徐桂琼,査九. 基于用户谱聚类的协同过滤推荐算法[J].计算机技术与发展,2014,24(09):59.
　LI Zhen-bo,XU Gui-qiong,ZHA Jiu. A Collaborative Filtering Recommendation Algorithm Based on User Spectral Clustering[J].,2014,24(09):59.
[14]蒋宗礼,隋少鹏. 基于领域本体和位置关系的信息检索模型[J].计算机技术与发展,2015,25(01):6.
　JIANG Zong-li,SUI Shao-peng. Information Retrieval Model Based on Domain Ontology and Position Relationship[J].,2015,25(09):6.
[15]王全民,王莉,曹建奇. 基于评论挖掘的改进的协同过滤推荐算法[J].计算机技术与发展,2015,25(10):24.
　WANG Quan-min,WANG Li,CAO Jian-qi. Improved Collaborative Filtering Recommendation Algorithm Based on Comments Mining[J].,2015,25(09):24.
[16]戴琼,周明全,付倩. 小篆文字的自动识别[J].计算机技术与发展,2016,26(03):1.
　DAI Qiong,ZHOU Ming-quan,FU Qian. Automatic Recognition of Xiaozhuan Fonts[J].,2016,26(09):1.
[17]白菊[],何聚厚[]. 应用于问答系统的Lucene相似度检索算法改进[J].计算机技术与发展,2017,27(11):79.
　BAI Ju[],HE Ju-hou[]. Improvement of Lucene Similarity Search Algorithm Applied in Question Answering System[J].,2017,27(09):79.

更新日期/Last Update: 2016-10-26