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Cross-temporal snapshot alignment for dynamic networks
In this paper, we study the task of cross-temporal snapshot alignment for dynamic networks. The goal of this task is to match …
Shangsong Liang, Shaowei Tang, Zaiqiao Meng, Qiang Zhang
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Mixture-of-Partitions: Infusing Large Biomedical Knowledge Graphs into BERT
Infusing factual knowledge into pre-trained models is fundamental for many knowledge-intensive tasks. In this paper, we proposed …
Zaiqiao Meng, Fangyu Liu, Thomas Hikaru Clark, Ehsan Shareghi, Nigel Collier
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Mixture-of-Partitions: Infusing Large Biomedical Knowledge Graphs into BERT
Few-Shot Table-to-Text Generation with Prototype Memory
Neural table-to-text generation models have achieved remarkable progress on an array of tasks. However, due to the data-hungry nature …
Yixuan Su, Zaiqiao Meng, Simon Baker, Nigel Collier
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Gaussian process with graph convolutional kernel for relational learning
Gaussian Process (GP) offers a principled non-parametric framework for learning stochastic functions. The generalization capability of …
Jinyuan Fang, Shangsong Liang, Zaiqiao Meng, Qiang Zhang
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Learning dynamic embeddings for temporal knowledge graphs
Representation learning for temporal knowledge graphs has attracted increasing attention in recent years. In this paper, we study the …
Siyuan Liao, Shangsong Liang, Zaiqiao Meng, Qiang Zhang
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Self-Alignment Pretraining for Biomedical Entity Representations
Despite the widespread success of self-supervised learning via masked language models (MLM), accurately capturing fine-grained semantic …
Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, Nigel Collier
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Self-Alignment Pretraining for Biomedical Entity Representations
Beta-rec: Build, evaluate and tune automated recommender systems
The field of recommender systems has rapidly evolved over the last few years, with significant advances made due to the in-flux of deep …
Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis, Siwei Liu, Yaxiong Wu, Xi Wang, Shangsong Liang, Yucheng Liang, Guangtao Zeng, Junhua Liang, Qiang Zhang
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Exploring data splitting strategies for the evaluation of recommendation models
Effective methodologies for evaluating recommender systems are critical, so that different systems can be compared in a sound manner. A …
Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis
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A heterogeneous graph neural model for cold-start recommendation
The users’ historical interactions usually contain their interests and purchase habits based on which personalised …
Siwei Liu, Iadh Ounis, Craig Macdonald, Zaiqiao Meng
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Jointly learning representations of nodes and attributes for attributed networks
Previous embedding methods for attributed networks aim at learning low-dimensional vector representations only for nodes but not for …
Zaiqiao Meng, Shangsong Liang, Xiangliang Zhang, Richard McCreadie, Iadh Ounis
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