Recent findings have shown multiple graph learning models, such as graph classification
and graph matching, are highly vulnerable to adversarial attacks, ie small input …

Context Mashup is emerging as a promising software development method for allowing
software developers to compose existing Web APIs to create new or value-added composite …

A recent study has shown that graph matching models are vulnerable to adversarial
manipulation of their input which is intended to cause a mismatching. Nevertheless, there is …

Network alignment, which aims at learning a matching between the same entities across
multiple information networks, often suffers challenges from feature inconsistency, high …

Recent literatures have shown that knowledge graph (KG) learning models are highly
vulnerable to adversarial attacks. However, there is still a paucity of vulnerability analyses of …

Recent studies have shown that graph learning models are highly vulnerable to adversarial
attacks, and network alignment methods are no exception. How to enhance the robustness …

The advent of social networks and activity networks affords us an opportunity of utilizing
explicit social information and activity information to improve the quality of recommendation …

Network alignment techniques, which aim to identify the same entities across multiple
networks, often suffer challenges from feature inconsistency to transitivity law preservation …

Utilizing graph analysis models and algorithms to exploit complex interactions over a
network of entities is emerging as an attractive network analytic technology. In this paper, we …

With continued advances in science and technology, big graph (or network) data, such as
World Wide Web, social networks, academic collaboration networks, transportation …