.png){kind=icon}
返回
CoRE: A Context-Aware Relation Extraction Method for Relation Completion
.png){kind=icon}
OA
AI
DOI：10.1109/TKDE.2013.148.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation R, RC attempts at linking entity pairs between two entity lists under the relation R. To accomplish the RC goals, we propose to formulate search queries for each query entity a based on some auxiliary information, so that to detect its target entity beta from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.
Keyword:
Context-aware relation extraction
relation completion
relation query expansion
期刊
IF:
10.4
论文数:
6.9K
被引数:
3.2W
机构
引用论文
One-year functional outcomes following major trauma: experience of a UK level 1 major trauma centre
.png){kind=icon}
PREAI
分享收藏
分享收藏
查看更多内容