[1]郭 强,谭菊仙,刘家祝.基于图嵌入的社交账号与知识图谱实体对齐[J].计算机技术与发展,2021,31(09):19-23.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 004]
　GUO Qiang,TAN Ju-xian,LIU Jia-zhu.Graph Embedding Based Alignment Between Social Media Account and Knowledge Graph Entity[J].,2021,31(09):19-23.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 004]
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基于图嵌入的社交账号与知识图谱实体对齐()

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

卷:
31
期数:
2021年09期
页码:
19-23
栏目:
大数据分析与挖掘
出版日期:
2021-09-10

文章信息/Info

Title:
Graph Embedding Based Alignment Between Social Media Account and Knowledge Graph Entity
文章编号:
1673-629X(2021)09-0019-05
作者:
郭 强; 谭菊仙; 刘家祝
江南计算技术研究所,江苏 无锡 214085
Author(s):
GUO Qiang; TAN Ju-xian; LIU Jia-zhu
Jiangnan Institute of Computing Technology,Wuxi 214085,China
关键词:
社交网络; 知识图谱; 数据融合; 图嵌入特征; 实体对齐
Keywords:
social network; knowledge graph; data fusion; graph embedding features; entity alignment
分类号:
TP391. 1
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 09. 004
摘要:
社交网络与知识图谱的之间的数据融合对于知识图谱构建和社交网络分析具有重要的应用价值,而社交账号与知识图谱实体的对齐是两类数据融合的关键。 针对社交账号与知识图谱实体的对齐问题,结合社交网络与知识图谱的结构特点,文中提出了一种基于图嵌入特征的社交账号实体对齐方法,旨在给定社交账号的情况下,能够在知识图谱中找到正确的对应实体。 该方法在目标实体选择阶段将社交关系子图映射成知识图谱子图,利用图嵌入特征选取子图中的核心实体集,并根据核心实体集构造特征向量,选用多层感知机作为分类器,从而确定社交账号所对应的目标实体。 使用基于Twitter 与 Wikidata 的实体对齐数据集进行了实验验证,通过与基线方法的对比,实验结果表明该方法能够达到较好的对齐效果。
Abstract:
The data fusion between social network and knowledge graph has important application value for knowledge graph construction and social network analysis,and the alignment of social account and knowledge graph entity is the key to the fusion of two kinds of data.In view of the alignment of social account and knowledge graph entity, combining the structure characteristics of social network and knowledge graph,we put forward a social account entity alignment method based on the embedded characteristics of the graph,so as to find the correct corresponding entity in the knowledge graph given the social account. This method maps the social relationship sub graph into a knowledge graph sub graph during the target entity selection stage,uses graph embedding features to select the core entity set in the sub graph,constructs the feature vector according to the core entity set,and choose the multi-layer perceptual machine as the classifier to determine the target entity corresponding to the social account. Experimental validation is performed by the entity alignment data set based on Twitter and Wiki data. By comparing with the baseline method,the experiment shows that the proposed method can achieve better alignment.

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[1]李桃陶,周斌,王忠振. 基于社交网络的图数据挖掘应用研究[J].计算机技术与发展,2014,24(10):6.
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　FANG Xuan[],CHEN Sheng-bo[],GONG Jing[][],et al. A Recommendation Algorithm Based on Social Influence[J].,2016,26(09):31.
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更新日期/Last Update: 2021-09-10