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- research-articleJuly 2024
Lightweight Embeddings for Graph Collaborative Filtering
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 1296–1306https://doi.org/10.1145/3626772.3657820Graph neural networks (GNNs) are currently one of the most performant and versatile collaborative filtering methods. Meanwhile, like in traditional collaborative filtering, owing to the use of an embedding table to represent each user/item entity as a ...
- research-articleJuly 2024
Poisoning Decentralized Collaborative Recommender System and Its Countermeasures
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 1712–1721https://doi.org/10.1145/3626772.3657814To make room for privacy and efficiency, the deployment of many recommender systems is experiencing a shift from central servers to personal devices, where the federated recommender systems (FedRecs) and decentralized collaborative recommender systems (...
- research-articleJuly 2024
CaseLink: Inductive Graph Learning for Legal Case Retrieval
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 2199–2209https://doi.org/10.1145/3626772.3657693In case law, the precedents are the relevant cases that are used to support the decisions made by the judges and the opinions of lawyers towards a given case. This relevance is referred to as the case-to-case reference relation. To efficiently find ...
- research-articleMay 2024JUST ACCEPTED
Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion
Visually-aware recommender systems have found widespread applications in domains where visual elements significantly contribute to the inference of users’ potential preferences. While the incorporation of visual information holds the promise of enhancing ...
- tutorialMay 2024
On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm
WWW '24: Companion Proceedings of the ACM on Web Conference 2024May 2024, Pages 1280–1283https://doi.org/10.1145/3589335.3641250Given the sheer volume of contemporary e-commerce applications, recommender systems (RSs) have gained significant attention in both academia and industry. However, traditional cloud-based RSs face inevitable challenges, such as resource-intensive ...
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- research-articleMay 2024
Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 3930–3939https://doi.org/10.1145/3589334.3645696In Location-based Social Networks (LBSNs), Point-of-Interest (POI) recommendation helps users discover interesting places. There is a trend to move from the conventional cloud-based model to on-device recommendations for privacy protection and reduced ...
- research-articleMay 2024
Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 3910–3918https://doi.org/10.1145/3589334.3645690Federated recommender systems (FedRecs) have gained significant attention for their potential to protect user's privacy by keeping user privacy data locally and only communicating model parameters/gradients to the server. Nevertheless, the currently ...
- research-articleMay 2024
Challenging Low Homophily in Social Recommendation
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 3476–3484https://doi.org/10.1145/3589334.3645460Social relations are leveraged to tackle the sparsity issue of user-item interaction data in recommendation under the assumption of social homophily. However, social recommendation paradigms predominantly focus on homophily based on user preferences. ...
- research-articleMay 2024
Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 3379–3387https://doi.org/10.1145/3589334.3645410As an indispensable personalized service within Location-Based Social Networks (LBSNs), the Point-of-Interest (POI) recommendation aims to assist individuals in discovering attractive and engaging places. However, the accurate recommendation capability ...
- research-articleMay 2024
Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 3139–3149https://doi.org/10.1145/3589334.3645337Cross-domain Recommendation (CDR) as one of the effective techniques in alleviating the data sparsity issues has been widely studied in recent years. However, previous works may cause domain privacy leakage since they necessitate the aggregation of ...
- research-articleApril 2024
OntoMedRec: Logically-pretrained model-agnostic ontology encoders for medication recommendation
AbstractRecommending medications with electronic health records (EHRs) is a challenging task for data-driven clinical decision support systems. Most existing models learnt representations for medical concepts based on EHRs and make recommendations with ...
- research-articleApril 2024
Portable graph-based rumour detection against multi-modal heterophily
Knowledge-Based Systems (KNBS), Volume 284, Issue CJan 2024https://doi.org/10.1016/j.knosys.2023.111310AbstractThe propagation of rumours on social media poses an important threat to societies, so that various techniques for graph-based rumour detection have been proposed recently. Existing works, however, are based on homophilic graphs: entities that are ...
Highlights- Identify the challenge of multi-modal heterophily for graph-based rumour detection.
- Propose a portable, multi-modal, and heterophily-aware neighbourhood aggregation.
- Light-weight graph transformer using only transformer encoder.
- research-articleApril 2024
HiTSKT: A hierarchical transformer model for session-aware knowledge tracing
Knowledge-Based Systems (KNBS), Volume 284, Issue CJan 2024https://doi.org/10.1016/j.knosys.2023.111300AbstractKnowledge tracing (KT) aims to leverage students’ learning histories to estimate their mastery levels on a set of pre-defined skills, based on which the corresponding future performance can be accurately predicted. In practice, a student’s ...
- research-articleMarch 2024
Budgeted Embedding Table For Recommender Systems
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data MiningMarch 2024, Pages 557–566https://doi.org/10.1145/3616855.3635778At the heart of contemporary recommender systems (RSs) are latent factor models that provide quality recommendation experience to users. These models use embedding vectors, which are typically of a uniform and fixed size, to represent users and items. As ...
- research-articleMarch 2024
Motif-based Prompt Learning for Universal Cross-domain Recommendation
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data MiningMarch 2024, Pages 257–265https://doi.org/10.1145/3616855.3635754Cross-Domain Recommendation (CDR) stands as a pivotal technology addressing issues of data sparsity and cold start by transferring general knowledge from the source to the target domain. However, existing CDR models suffer limitations in adaptability ...
- research-articleMarch 2024
Defense Against Model Extraction Attacks on Recommender Systems
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data MiningMarch 2024, Pages 949–957https://doi.org/10.1145/3616855.3635751The robustness of recommender systems has become a prominent topic within the research community. Numerous adversarial attacks have been proposed, but most of them rely on extensive prior knowledge, such as all the white-box attacks or most of the black-...
- research-articleFebruary 2024
- research-articleJanuary 2024
Heterogeneous decentralised machine unlearning with seed model distillation
CAAI Transactions on Intelligence Technology (CIT2), Volume 9, Issue 3June 2024, Pages 608–619https://doi.org/10.1049/cit2.12281AbstractAs some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model, personalised IoT service providers have to put unlearning functionality into their consideration. The ...
- research-articleDecember 2023
Manipulating Visually Aware Federated Recommender Systems and Its Countermeasures
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3Article No.: 64, Pages 1–26https://doi.org/10.1145/3630005Federated recommender systems (FedRecs) have been widely explored recently due to their capability to safeguard user data privacy. These systems enable a central server to collaboratively learn recommendation models by sharing public parameters with ...
- research-articleDecember 2023
Isomorphic Graph Embedding for Progressive Maximal Frequent Subgraph Mining
- Thanh Toan Nguyen,
- Thanh Tam Nguyen,
- Thanh Hung Nguyen,
- Hongzhi Yin,
- Thanh Thi Nguyen,
- Jun Jo,
- Quoc Viet Hung Nguyen
ACM Transactions on Intelligent Systems and Technology (TIST), Volume 15, Issue 1Article No.: 9, Pages 1–26https://doi.org/10.1145/3630635Maximal frequent subgraph mining (MFSM) is the task of mining only maximal frequent subgraphs, i.e., subgraphs that are not a part of other frequent subgraphs. Although many intelligent systems require MFSM, MFSM is challenging compared to frequent ...