Text-enhanced and implicit reasoning methods are proposed for answering questions over
incomplete knowledge graph (KG), whereas prior studies either rely on external resources …

Abstract Knowledge graph question answering (KGQA) aims to answer natural language
questions from structured knowledge graphs (KGs). Traditional KQGA methods are usually …

Existing embedded multi-hop Question Answering over Knowledge Graph (KGQA) methods
attempted to handle Knowledge Graph (KG) sparsity using Knowledge Graph Embedding …

Multi-hop question answering from knowledge graphs has gained a growing attention in the
past few years due to its vast applications in AI. Existing approaches in this regard mostly …

Driven by the new generation of information technologies such as the Internet of Things and
mobile communications, smart education is an important strategy for future educational …

Multi-hop question answering over knowledge graph utilizes the knowledge graph (KG)
structure to infer answers. However, KG often lacks edges in the reasoning path from the …

Existing multi-hop knowledge graph question answering (KGQA) methods, which attempt to
mitigate knowledge graph (KG) sparsity by introducing external text repositories instead of …

Knowledge Graph Question Answering (KGQA) is a fundamental task in Knowledge Graph
(KG). Existing works of KGQA deduce path information from the neighborhood of the …

With the influence of various comprehensive factors such as people's diet and living habits
and the external environment, lung cancer has become a high-incidence and high-risk …