基于多重序列所有公共子序列的启发式算法度量多图的相似度

doi:10.13229/j.cnki.jdxbgxb20170302

吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (2): 526-532.doi: 10.13229/j.cnki.jdxbgxb20170302

基于多重序列所有公共子序列的启发式算法度量多图的相似度

王旭^{1, 2}, 欧阳继红^{1, 2}, 陈桂芬³

1.吉林大学计算机科学与技术学院,长春130012;
2.吉林大学符号计算与知识工程教育部重点实验室,长春130012;
3.吉林农业大学信息技术学院,长春 130118

收稿日期:2017-03-30 出版日期:2018-03-01 发布日期:2018-03-01
通讯作者: 欧阳继红(1964-),女,教授,博士生导师. 研究方向:数据挖掘,时空推理. E-mail:ouyj@jlu.edu.cn
作者简介:王旭(1982-),男,博士研究生. 研究方向:数据挖掘,图挖掘. E-mail:75014557@qq.com
基金资助:
国家自然科学基金项目(61472157,61602204,6152198)

Heuristic algorithm of all common subsequences of multiple sequences for measuring multiple graphs similarity

WANG Xu^{1, 2}, OUYANG Ji-hong^{1, 2}, CHEN Gui-fen³

1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;
3.College of Information Technology, Jilin Agricultural University, Changchun 130118, China

Received:2017-03-30 Online:2018-03-01 Published:2018-03-01

摘要/Abstract

摘要： 提出了启发式A^*算法度量任意多个图的相似度方法,该算法将多图表示多重序列,在多重序列的匹配点上计算多重序列的所有公共子序列数,得到的所有公共子序列数用来度量多图的相似度。该算法避免了在非匹配点上的冗余计算,最大化后缀序列的所有公共子序列数的启发函数值,将访问的节点限制在两个序列匹配的子集,减少了计算节点的个数。与现有度量图的相似度方法相比,该算法不仅可以度量任意多个图的相似度,而且计算过程简单,通过启发信息的引导能够快速地度量多图的相似度。

关键词: 人工智能, 多图相似度, 启发式算法, 所有公共子序列, 多重序列, 匹配

Abstract: A heuristic algorithm A^* for measuring the similarity of multiple graphs is proposed. In this algorithm, the multiple graphs are represented as multiple sequences, then the number of all common subsequences in the matches of the multiple graphs is calculated, and this number is used to measure the similarity of the multiple graphs. This algorithm avoids the redundant calculations in non-matches of multiple graphs, maximizes the heuristic function value of all common subsequences of the suffixes sequences, limits the search nodes to the subset of matches between two sequences, thus reducing the number of the calculation nodes. Compared with the existing graph similarity methods, the proposed algorithm can not only measure the similarity of multiple graphs, but also simplify the calculation process. The similarity of multiple graphs can be quickly measured using this algorithm with the boot of the heuristic information.

Key words: artificial intelligence, multiple graph similarity, heuristic algorithm, all common subsequences, multiple sequences, matches

中图分类号:

TP18

王旭, 欧阳继红, 陈桂芬. 基于多重序列所有公共子序列的启发式算法度量多图的相似度[J]. 吉林大学学报(工学版), 2018, 48(2): 526-532.

WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Heuristic algorithm of all common subsequences of multiple sequences for measuring multiple graphs similarity[J]. 吉林大学学报(工学版), 2018, 48(2): 526-532.

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基于多重序列所有公共子序列的启发式算法度量多图的相似度

Heuristic algorithm of all common subsequences of multiple sequences for measuring multiple graphs similarity

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