1) relation extraction
关系抽取
1.
The Research of Chinese Named Entity Recognition and Its Relation Extraction;
中文命名实体识别及其关系抽取研究
2.
Application of discourse analysis in entity semantic relation extraction
语篇分析在实体语义关系抽取中的应用
2) interaction extraction
关系抽取
1.
Protein-Protein Interaction Extraction System Based on SVM and Link Parse;
基于SVM和链接分析的蛋白质关系抽取系统
2.
Research of protein-protein interaction extraction based on semi-supervised learning
基于半监督学习的蛋白质关系抽取研究
3.
This paper presents a method for protein-protein interaction extraction from biomedical literature using a support vector machine(SVM).
提出了一种基于支持向量机(SVM)的蛋白质(基因)交互作用关系抽取方法。
3) entity relation extraction
实体关系抽取
1.
Research on Kernel Based Entity Relation Extraction;
基于核函数的命名实体关系抽取技术研究
4) semantic relation extraction
语义关系抽取
1.
Research on Semi-Supervised Semantic Relation Extraction between Named Entities;
基于弱指导学习的实体间语义关系抽取研究
2.
The present feature vector based approach for semantic relation extraction can hardly be improved simply by mining new features.
语义关系抽取是信息抽取中的一个重要的研究领域。
3.
This paper presents a novel method of using bootstrapping for the task of weakly-supervised semantic relation extraction.
提出一种基于Bootstrapping的弱指导语义关系抽取方法。
5) PPI
蛋白质关系抽取
1.
Protein-protein interaction (PPI) extraction as a subtask of text mining is not only helpful to build protein relation network, but also to predict protein function and design new drugs.
随着生物医学文献的不断增加,大量的有用信息埋藏在文本里,因此生物医学方面的文本挖掘成为当今研究的热点问题,蛋白质关系抽取作为文本挖掘的子任务,不仅对蛋白质知识网络的构建有帮助,同时对蛋白质关系的预测,新药的研制均具有非常重要的意义。
6) comparative relations extraction
比较关系抽取
1.
Automatic comparative sentences identification and comparative relations extraction contribute to opinion mining and information recommendation.
在此基础上,本文通过选取比较主体、比较客体及其上下文的词、词性、位置、语义以及比较属性的领域知识等特征,利用条件随机域模型进行中文比较关系抽取。
补充资料：经济关系(见生产关系)
经济关系(见生产关系)
economical relation
1 ingji gU口nxj经济关系(eeonomieal relation)系。见生产关
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条