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Zhang, S. (author), Hanjalic, A. (author), Wang, H. (author)Nodal spreading influence is the capability of a node to activate the rest of the network when it is the seed of spreading. Combining nodal properties (centrality metrics) derived from local and global topological information respectively has been shown to better predict nodal influence than using a single metric. In this work, we investigate...journal article 2024
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Li, Roger Zhe (author), Urbano, Julián (author), Hanjalic, A. (author)Mainstream bias, where some users receive poor recommendations because their preferences are uncommon or simply because they are less active, is an important aspect to consider regarding fairness in recommender systems. Existing methods to mitigate mainstream bias do not explicitly model the importance of these non-mainstream users or, when...conference paper 2023
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Zhang, T. (author), El Ali, Abdallah (author), Wang, Chen (author), Hanjalic, A. (author), Cesar, Pablo (author)Instead of predicting just one emotion for one activity (e.g., video watching), fine-grained emotion recognition enables more temporally precise recognition. Previous works on fine-grained emotion recognition require segment-by-segment, fine-grained emotion labels to train the recognition algorithm. However, experiments to collect these...journal article 2023
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Zou, L. (author), Zhan, Xiu xiu (author), Sun, Jie (author), Hanjalic, A. (author), Wang, H. (author)Temporal networks refer to networks like physical contact networks whose topology changes over time. Predicting future temporal network is crucial e.g., to forecast the epidemics. Existing prediction methods are either relatively accurate but black-box, or white-box but less accurate. The lack of interpretable and accurate prediction methods...journal article 2022
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Fernández Robledo, O. (author), Zhan, X. (author), Hanjalic, A. (author), Wang, H. (author)Multiple network embedding algorithms have been proposed to perform the prediction of missing or future links in complex networks. However, we lack the understanding of how network topology affects their performance, or which algorithms are more likely to perform better given the topological properties of the network. In this paper, we...journal article 2022
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Zhang, T. (author), El Ali, Abdallah (author), Hanjalic, A. (author), Cesar, Pablo (author)Fine-grained emotion recognition can model the temporal dynamics of emotions, which is more precise than predicting one emotion retrospectively for an activity (e.g., video clip watching). Previous works require large amounts of continuously annotated data to train an accurate recognition model, however experiments to collect such large...journal article 2022
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Subramanyam, S. (author), Viola, Irene (author), Jansen, Jack (author), Alexiou, Evangelos (author), Hanjalic, A. (author), Cesar, Pablo (author)Technological advances in head-mounted displays and novel real-time 3D acquisition and reconstruction solutions have fostered the development of 6 Degrees of Freedom (6DoF) teleimmersive systems for social VR applications. Point clouds have emerged as a popular format for such applications, owing to their simplicity and versatility; yet,...conference paper 2022
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Zhang, Jian (author), Hanjalic, A. (author), Jain, Ramesh (author), Hua, Xiansheng (author), Satoh, Shin'ichi (author), Yao, Yazhou (author), Zeng, Dan (author)This special issue provides a premier forum for researchers in multimedia big data to share challenges and recent advancements in learning from noisy multimedia data. The multimedia age and its proliferation of devices and platforms is fueling exponential data growth. As computational power and deep learning algorithms rapidly evolve, the web...review 2022
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Das, B. (author), Hanjalic, A. (author), Isufi, E. (author)Data processing over graphs is usually done on graphs of fixed size. However, graphs often grow with new nodes arriving over time. Knowing the connectivity information of these nodes, and thus, the expanded graph is crucial for processing data over the expanded graph. In its absence, its inference and the subsequent data processing become...journal article 2022
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Xu, Xing (author), Lin, Kaiyi (author), Yang, Yang (author), Hanjalic, A. (author), Shen, Heng Tao (author)Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn compatible cross-modal features, is becoming the research hotspot. However, the existing cross...journal article 2022
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Li, Roger Zhe (author), Urbano, Julián (author), Hanjalic, A. (author)In a collaborative-filtering recommendation scenario, biases in the data will likely propagate in the learned recommendations. In this paper we focus on the so-called mainstream bias: the tendency of a recommender system to provide better recommendations to users who have a mainstream taste, as opposed to non-mainstream users. We propose NAECF,...conference paper 2021
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Wang, X. (author), Qiao, T. (author), Zhu, Jihua (author), Hanjalic, A. (author), Scharenborg, O.E. (author)Text-based technologies, such as text translation from one language to another, and image captioning, are gaining popularity. However, approximately half of the world's languages are estimated to be lacking a commonly used written form. Consequently, these languages cannot benefit from text-based technologies. This paper presents 1) a new...journal article 2021
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Li, Roger Zhe (author), Urbano, Julián (author), Hanjalic, A. (author)Direct optimization of IR metrics has often been adopted as an approach to devise and develop ranking-based recommender systems. Most methods following this approach (e.g. TFMAP, CLiMF, Top-N-Rank) aim at optimizing the same metric being used for evaluation, under the assumption that this will lead to the best performance. A number of studies...conference paper 2021
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Isufi, E. (author), Pocchiari, Matteo (author), Hanjalic, A. (author)Graph convolutions, in both their linear and neural network forms, have reached state-of-the-art accuracy on recommender system (RecSys) benchmarks. However, recommendation accuracy is tied with diversity in a delicate trade-off and the potential of graph convolutions to improve the latter is unexplored. Here, we develop a model that learns...journal article 2021
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Urbano, Julián (author), Corsi, M. (author), Hanjalic, A. (author)Statistical significance tests are the main tool that IR practitioners use to determine the reliability of their experimental evaluation results. The question of which test behaves best with IR evaluation data has been around for decades, and has seen all kinds of results and recommendations. Definitive answer to this question has recently...conference paper 2021
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Slokom, M. (author), Hanjalic, A. (author), Larson, M.A. (author)In this paper, we propose a new privacy solution for the data used to train a recommender system, i.e., the user–item matrix. The user–item matrix contains implicit information, which can be inferred using a classifier, leading to potential privacy violations. Our solution, called Personalized Blurring (PerBlur), is a simple, yet effective,...journal article 2021
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Wang, X. (author), Qiao, T. (author), Zhu, Jihua (author), Hanjalic, A. (author), Scharenborg, O.E. (author)An estimated half of the world’s languages do not have a written form, making it impossible for these languages to benefit from any existing text-based technologies. In this paper, a speech-to-image generation (S2IG) framework is proposed which translates speech descriptions to photo-realistic images without using any text information, thus...conference paper 2020
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Zhang, T. (author), Ali, Abdallah El (author), Chen, C. (author), Hanjalic, A. (author), Cesar, Pablo (author)Recognizing user emotions while they watch short-form videos anytime and anywhere is essential for facilitating video content customization and personalization. However, most works either classify a single emotion per video stimuli, or are restricted to static, desktop environments. To address this, we propose a correlation-based emotion...journal article 2020
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Zhan, X. (author), Hanjalic, A. (author), Wang, H. (author)In this paper, we explore how to effectively suppress the diffusion of (mis)information via blocking/removing the temporal contacts between selected node pairs. Information diffusion can be modelled as, e.g., an SI (Susceptible-Infected) spreading process, on a temporal social network: an infected (information possessing) node spreads the...conference paper 2020
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Song, Jingkuan (author), He, Tao (author), Gao, Lianli (author), Xu, Xing (author), Hanjalic, A. (author), Shen, Heng Tao (author)Binary codes have often been deployed to facilitate large-scale retrieval tasks, but not that often for image compression. In this paper, we propose a unified framework, BGAN+, that restricts the input noise variable of generative adversarial networks to be binary and conditioned on the features of each input image, and simultaneously learns...journal article 2020