6 papers
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature
Cuiying Huo, Di Jin, Chundong Liang +3
Trust evaluation is critical for many applications such as cyber security, social communication and recommender systems. Users and trust relationships among them can be seen as a g…
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation
Di Jin, Bunyamin Sisman, Hao Wei +2
Multi-source entity linkage focuses on integrating knowledge from multiple sources by linking the records that represent the same real world entity. This is critical in high-impact…
Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue Systems
Di Jin, Shuyang Gao, Seokhwan Kim +2
Most prior work on task-oriented dialogue systems is restricted to supporting domain APIs. However, users may have requests that are out of the scope of these APIs. This work focus…
Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing
Neil Getty, Thomas Brettin, Dong Jin +2
We explore three representative lines of research and demonstrate the utility of our methods on a classification benchmark of brain cancer MRI data. First, we present a capsule net…
Advancing PICO Element Detection in Biomedical Text via Deep Neural Networks
Di Jin, Peter Szolovits
In evidence-based medicine (EBM), defining a clinical question in terms of the specific patient problem aids the physicians to efficiently identify appropriate resources and search…
Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts
Di Jin, Peter Szolovits
Prevalent models based on artificial neural network (ANN) for sentence classification often classify sentences in isolation without considering the context in which sentences appea…