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most citedExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions

12 citations · 35 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.SI2023

New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs

Raphaël Romero, Tijl De Bie, Jefrey Lijffijt

There is a fast-growing body of research on predicting future links in dynamic networks, with many new algorithms. Some benchmark data exists, and performance evaluations commonly…

cs.SI2021

Adversarial Robustness of Probabilistic Network Embedding for Link Prediction

Xi Chen, Bo Kang, Jefrey Lijffijt +1

In today's networked society, many real-world problems can be formalized as predicting links in networks, such as Facebook friendship suggestions, e-commerce recommendations, and t…

cs.SI2020

CSNE: Conditional Signed Network Embedding

Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt +1

Signed networks are mathematical structures that encode positive and negative relations between entities such as friend/foe or trust/distrust. Recently, several papers studied the…

cs.SI2020

Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach

Junning Deng, Bo Kang, Jefrey Lijffijt +1

The connectivity structure of graphs is typically related to the attributes of the nodes. In social networks for example, the probability of a friendship between two people depends…

cs.SI2019

Mining Subjectively Interesting Attributed Subgraphs

Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt +3

Community detection in graphs, data clustering, and local pattern mining are three mature fields of data mining and machine learning. In recent years, attributed subgraph mining is…

cs.SI2019

Opinion Dynamics with Backfire Effect and Biased Assimilation

Xi Chen, Panayiotis Tsaparas, Jefrey Lijffijt +1

The democratization of AI tools for content generation, combined with unrestricted access to mass media for all (e.g. through microblogging and social media), makes it increasingly…