Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion

Q Li, S Guo, Y Chen, C Ji, J Sheng, J Li - arxiv preprint arxiv:2403.04521, 2024 - arxiv.org
Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation
given its few-shot reference entity pairs. The side effect of noises due to the uncertainty of …

An efficient approach for faster matching of approximate patterns in graphs

MG Khan, Z Halim, AR Baig - Knowledge-Based Systems, 2023 - Elsevier
Graphs have proven to be an efficient problem representation scheme in many real-world
applications and can serve to address mining of patterns in large volumes of data. This work …

A CAD model retrieval framework based on correlation network and relevance ranking

B Ji, J Zhang, Y Li, W Tang - Journal of Mechanical Science and …, 2023 - Springer
The computer-aided design (CAD) models contain abundant domain knowledge, either
structure, material, or process information. An efficient retrieval ability for these reusable …

A Weakly Supervised Academic Search Model Based on Knowledge‐Enhanced Feature Representation

M Xu, J Du, F Kou, M Liang, X Xu… - … and Mobile Computing, 2021 - Wiley Online Library
Internet of Things search has great potential applications with the rapid development of
Internet of Things technology. Combining Internet of Things technology and academic …

FPX-G: first person exploration for graph

T Komamizu, S Ito, Y Ogawa… - 2021 IEEE 4th …, 2021 - ieeexplore.ieee.org
Data exploration is a fundamental user task in the information seeking process. In data
exploration, users have ambiguous information needs, and they traverse across the data for …

Predicting most influential paper award using citation count

F Sadaf, MH Shahid, MA Islam - 2021 International conference …, 2021 - ieeexplore.ieee.org
The early identification of the influential papers is of great significance for assessing the
scientific achievements of researchers and institutions as it can help in addressing the …