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- research-articleAugust 2024JUST ACCEPTED
- research-articleJuly 2024JUST ACCEPTED
RevGNN: Negative Sampling Enhanced Contrastive Graph Learning for Academic Reviewer Recommendation
Acquiring reviewers for academic submissions is a challenging recommendation scenario. Recent graph learning-driven models have made remarkable progress in the field of recommendation, but their performance in the academic reviewer recommendation task may ...
- research-articleJune 2024JUST ACCEPTED
- research-articleMay 2024
Average User-Side Counterfactual Fairness for Collaborative Filtering
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 5Article No.: 140, Pages 1–26https://doi.org/10.1145/3656639Recently, the user-side fairness issue in Collaborative Filtering (CF) algorithms has gained considerable attention, arguing that results should not discriminate an individual or a sub-user group based on users’ sensitive attributes (e.g., gender). ...
- research-articleApril 2024
Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 5Article No.: 128, Pages 1–31https://doi.org/10.1145/3653673Point-of-Interest (POI) recommendation, an important research hotspot in the field of urban computing, plays a crucial role in urban construction. While understanding the process of users’ travel decisions and exploring the causality of POI choosing is ...
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- research-articleApril 2024
DHyper: A Recurrent Dual Hypergraph Neural Network for Event Prediction in Temporal Knowledge Graphs
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 5Article No.: 129, Pages 1–23https://doi.org/10.1145/3653015Event prediction is a vital and challenging task in temporal knowledge graphs (TKGs), which have played crucial roles in various applications. Recently, many graph neural networks based approaches are proposed to model the graph structure information in ...
- research-articleApril 2024
ELAKT: Enhancing Locality for Attentive Knowledge Tracing
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 112, Pages 1–27https://doi.org/10.1145/3652601Knowledge tracing models based on deep learning can achieve impressive predictive performance by leveraging attention mechanisms. However, there still exist two challenges in attentive knowledge tracing (AKT): First, the mechanism of classical models of ...
- research-articleApril 2024
Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 110, Pages 1–28https://doi.org/10.1145/3651158Career mobility analysis aims at understanding the occupational movement patterns of talents across distinct labor market entities, which enables a wide range of talent-centered applications, such as job recommendation, labor demand forecasting, and ...
- research-articleApril 2024
Filter-based Stance Network for Rumor Verification
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 108, Pages 1–28https://doi.org/10.1145/3649462Rumor verification on social media aims to identify the truth value of a rumor, which is important to decrease the detrimental public effects. A rumor might arouse heated discussions and replies, conveying different stances of users that could be helpful ...
- research-articleMarch 2024
Token-Event-Role Structure-Based Multi-Channel Document-Level Event Extraction
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 104, Pages 1–27https://doi.org/10.1145/3643885Document-level event extraction is a long-standing challenging information retrieval problem involving a sequence of sub-tasks: entity extraction, event type judgment, and event type-specific multi-event extraction. However, addressing the problem as ...
- research-articleMarch 2024
Can Perturbations Help Reduce Investment Risks? Risk-aware Stock Recommendation via Split Variational Adversarial Training
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 101, Pages 1–28https://doi.org/10.1145/3643131In the stock market, a successful investment requires a good balance between profits and risks. Based on the learning to rank paradigm, stock recommendation has been widely studied in quantitative finance to recommend stocks with higher return ratios for ...
- research-articleMarch 2024
- research-articleJanuary 2024
SMLP4Rec: An Efficient All-MLP Architecture for Sequential Recommendations
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3Article No.: 86, Pages 1–23https://doi.org/10.1145/3637871Self-attention models have achieved the state-of-the-art performance in sequential recommender systems by capturing the sequential dependencies among user–item interactions. However, they rely on adding positional embeddings to the item sequence to retain ...
- research-articleJanuary 2024
Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3Article No.: 82, Pages 1–29https://doi.org/10.1145/3633202Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic. However, there exists an inescapable risk of privacy leakage in the fine-grained user mobility trajectories required ...
- research-articleDecember 2023
rHDP: An Aspect Sharing-Enhanced Hierarchical Topic Model for Multi-Domain Corpus
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3Article No.: 71, Pages 1–31https://doi.org/10.1145/3631352Learning topic hierarchies from a multi-domain corpus is crucial in topic modeling as it reveals valuable structural information embedded within documents. Despite the extensive literature on hierarchical topic models, effectively discovering inter-topic ...
- research-articleNovember 2023
Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 2Article No.: 58, Pages 1–26https://doi.org/10.1145/3626091Session-based recommendation (SBR) systems aim to utilize the user’s short-term behavior sequence to predict the next item without the detailed user profile. Most recent works try to model the user preference by treating the sessions as between-item ...
- research-articleNovember 2023
Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 2Article No.: 51, Pages 1–29https://doi.org/10.1145/3618106Review-based recommender systems explore semantic aspects of users’ preferences by incorporating user-generated reviews into rating-based models. Recent works have demonstrated the potential of review information to improve the recommendation capacity. ...
- research-articleNovember 2023
Heterogeneous Evolution Network Embedding with Temporal Extension for Intelligent Tutoring Systems
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 2Article No.: 45, Pages 1–28https://doi.org/10.1145/3617828Graph embedding (GE) aims to acquire low-dimensional node representations while maintaining the graph’s structural and semantic attributes. Intelligent tutoring systems (ITS) signify a noteworthy achievement in the fusion of AI and education. Utilizing GE ...
- research-articleNovember 2023
Alleviating Video-length Effect for Micro-video Recommendation
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 2Article No.: 44, Pages 1–24https://doi.org/10.1145/3617826Micro-video platforms such as TikTok are extremely popular nowadays. One important feature is that users no longer select interested videos from a set; instead, they either watch the recommended video or skip to the next one. As a result, the time length ...
- research-articleNovember 2023