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Structack: Structure-based Adversarial Attacks on Graph Neural Networks.

, , , , , и . HT, стр. 111-120. ACM, (2021)

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My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music., , , и . ASONAM, стр. 447-454. ACM, (2021)Structack: Structure-based Adversarial Attacks on Graph Neural Networks., , , , , и . HT, стр. 111-120. ACM, (2021)Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering., , , , , и . ISMIS, том 12117 из Lecture Notes in Computer Science, стр. 181-191. Springer, (2020)Beyond-Accuracy: A Review on Diversity, Serendipity and Fairness in Recommender Systems Based on Graph Neural Networks., , , и . CoRR, (2023)Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings., , , , и . CoRR, (2023)AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments., , , , , и . ECAI, том 392 из Frontiers in Artificial Intelligence and Applications, стр. 4491-4494. IOS Press, (2024)Cross-platform analysis of user comments in YouTube videos linked on Reddit conspiracy theory forum., , и . CoRR, (2021)On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks., , , , и . COMPLEX NETWORKS (2), том 944 из Studies in Computational Intelligence, стр. 15-26. Springer, (2020)Trust-based collaborative filtering: tackling the cold start problem using regular equivalence., , , и . RecSys, стр. 446-450. ACM, (2018)Should we embed?: a study on the online performance of utilizing embeddings for real-time job recommendations., , , , и . RecSys, стр. 496-500. ACM, (2019)