Abstract Knowledge is a formal way of understanding the world, providing human-level
cognition and intelligence for the next-generation artificial intelligence (AI). An effective way …

Attention mechanisms are often used in deep neural networks for distantly supervised
relation extraction (DS-RE) to distinguish valid from noisy instances. However, traditional 1 …

Document-level relation extraction (RE) is a more challenging task providing a new
perspective to solve larger and more complex text mining work. Recent document-level RE …

Relation classification is a crucial ingredient in numerous information-extraction systems
and has attracted a great deal of attention in recent years. Traditional approaches largely …

Distant supervision (DS) has become an efficient approach for relation extraction (RE) to
alleviate the lack of labeled examples in supervised learning. In this paper, we propose a …

Natural language processing (NLP) is the best solution to extensive, unstructured, complex,
and diverse network big data for counter-terrorism. Through the text analysis, it is the basis …

Relation extraction is one of the most important tasks in information extraction. The
traditional works either use sentences or surface patterns (ie, the shortest dependency paths …

Many recently proposed relation extraction methods are based on distantly supervised
learning. They use data from existing knowledge bases as training data. Although the …

为了提高对话中实体对的关系抽取能力, 将依存关系引入到异构图注意力网络中, 提出了DEP
GAT 模型. 首先, 通过预处理层获取每个词的基本特征, 然后在话语编码层实现上下文特征的 …

A multi-party dialogue relationship extraction model that integrates character reference
information is proposed based on a previous model of graph attention network. Specifically …