Information retrieval: recent advances and beyond
KA Hambarde, H Proenca - IEEE Access, 2023 - ieeexplore.ieee.org
This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …
utilized in the first and second stages of the typical information retrieval processing chain …
[PDF][PDF] Deep graph structure learning for robust representations: A survey
Abstract Graph Neural Networks (GNNs) are widely used for analyzing graph-structured
data. Most GNN methods are highly sensitive to the quality of graph structures and usually …
data. Most GNN methods are highly sensitive to the quality of graph structures and usually …
Mining latent structures for multimedia recommendation
Multimedia content is of predominance in the modern Web era. Investigating how users
interact with multimodal items is a continuing concern within the rapid development of …
interact with multimodal items is a continuing concern within the rapid development of …
Evidence-aware fake news detection with graph neural networks
The prevalence and perniciousness of fake news has been a critical issue on the Internet,
which stimulates the development of automatic fake news detection in turn. In this paper, we …
which stimulates the development of automatic fake news detection in turn. In this paper, we …
Latent structure mining with contrastive modality fusion for multimedia recommendation
Multimedia contents are of predominance in the modern Web era. Recent years have
witnessed growing research interests in multimedia recommendation, which aims to predict …
witnessed growing research interests in multimedia recommendation, which aims to predict …
Adversarial contrastive learning for evidence-aware fake news detection with graph neural networks
The prevalence and perniciousness of fake news have been a critical issue on the Internet,
which stimulates the development of automatic fake news detection in turn. In this paper, we …
which stimulates the development of automatic fake news detection in turn. In this paper, we …
Animating images to transfer clip for video-text retrieval
Recent works show the possibility of transferring the CLIP (Contrastive Language-Image
Pretraining) model for video-text retrieval with promising performance. However, due to the …
Pretraining) model for video-text retrieval with promising performance. However, due to the …
How can graph neural networks help document retrieval: A case study on cord19 with concept map generation
Graph neural networks (GNNs), as a group of powerful tools for representation learning on
irregular data, have manifested superiority in various downstream tasks. With unstructured …
irregular data, have manifested superiority in various downstream tasks. With unstructured …
Relation-aware heterogeneous graph for user profiling
User profiling has long been an important problem that investigates user interests in many
real applications. Some recent works regard users and their interacted objects as entities of …
real applications. Some recent works regard users and their interacted objects as entities of …
Interpretable Fake News Detection with Graph Evidence
Automatic detection of fake news has received widespread attentions over recent years. A
pile of efforts has been put forward to address the problem with high accuracy, while most of …
pile of efforts has been put forward to address the problem with high accuracy, while most of …