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Table 10 A list of research gaps and future research directions

From: A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions

Sr. no.

Research gaps

Future directions

1

Lack of ready datasets

Inconsistent Datasets

Domain Adaptation

2

Inefficient and time-consuming feature extraction task

Improving Text Classification

Here combining, deep learning and machine learning methods like GNNs to increase classification accuracy

3

Accuracy of Existing Systems/Models

Identification of Type of structure, i.e., homogenous heterogeneous

Deep Learning models such as GCN, GAT, and GraphSAGE