Towards a Semantic Keyword Search over Industrial Knowledge Graphs

被引：0
|
作者：
Cheng, Gong [1 ]
Kharlamov, Evgeny [2 ]
机构：
[1] Nanjing Univ, Natl Key Lab Novel Software Technol, Nanjing, Jiangsu, Peoples R China
[2] Univ Oxford, Dept Comp Sci, Oxford, England
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2017年
基金：
英国工程与自然科学研究理事会;
关键词：
keyword search; knowledge graph; cohesiveness; completeness; semantics; graph search; ACCESS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Knowlege graphs have become powerful assets for enhancing search and data integration and are now widely used in both academia and industry. Existing semantics of keyword search over knowledge graphs, especially in industrial context, has limitations. In this extended abstract we discuss these limitations and ingredients for alternative semantics.
引用
收藏
页码：1698 / 1700
页数：3
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