Due to the inception of Web 2.0 and freedom to facilitate the dissemination of information,
sharing views, expressing opinions with regards to current world level events, services …

Abstract Recently, reinforcement learning (RL)-based methods have achieved remarkable
progress in both effectiveness and interpretability for complex question answering over …

Aiming at the problem of insufficient knowledge service in the field of bridge inspection, this
paper proposes a knowledge graph question answering (KGQA) model by using BERT and …

Abstract Knowledge graph representation learning (KGRL) aims to infer the missing links
between target entities based on existing triples. Graph neural networks (GNNs) have been …

Broad learning system (BLS) has been proposed as an alternative method of deep learning.
The architecture of BLS is that the input is randomly mapped into series of feature spaces …

Abstract Currently, Knowledge Base Question Answering (KBQA) is an important research
topic in the fields of information retrieval (IR) and natural language processing (NLP). The …

Abstract Knowledge base question answering aims to answer natural language questions
by querying external knowledge base, which has been widely applied to many real-world …

Question answering over knowledge base (KBQA) is a powerful tool to extract answers from
graph-like knowledge bases. Here, we present ComQA-a three-phase KBQA framework by …

Event argument extraction, which aims to identify arguments of specific events and label
their roles, is a challenging subtask of event extraction. Previous approaches solve this …

Temporal knowledge graph embedding (TKGE) aims to learn the embedding of entities and
relations in a temporal knowledge graph (TKG). Although the previous graph neural …