Zhen Zhang

Learning Temporal Interaction Graph Embedding via Coupled Memory Networks

2020

Graph embedding has become the research focus in both academic and industrial communities due to its powerful capabilities. The majority of existing work overwhelmingly learn node embeddings in the context of static, plain or attributed, …

Using Deep Time Delay Neural Network for Slot Filling in Spoken Language Understanding

2020 · Symmetry

Modeling the context of a target word is of fundamental importance in predicting the semantic label for slot filling task in Spoken Language Understanding (SLU). Although Recurrent Neural Network (RNN) has shown to successfully achieve …

Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification

2020 · arXiv (Cornell University)

Graph classification aims to extract accurate information from graph-structured data for classification and is becoming more and more important in graph learning community. Although Graph Neural Networks (GNNs) have been successfully applied to graph classification …

HVMM: A Holistic Virtual Machine Management Strategy for Cloud Data Centers

2023 · IEEE Transactions on Network and Service Management

Cloud computing has emerged as an infrastructure in the era of digital economy and has been widely applied in various fields. Virtual Machine(VM) management is the key mechanism in a Cloud Data Center(CDC). A typical …

LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using Uncertainty

2024 · arXiv (Cornell University)

Named Entity Recognition (NER) serves as a fundamental task in natural language understanding, bearing direct implications for web content analysis, search engines, and information retrieval systems. Fine-tuned NER models exhibit satisfactory performance on standard NER …

Improving text classification via computing category correlation matrix from text graph

2024 · Computer Speech & Language

In text classification task , models have shown remarkable accuracy across various datasets. However, confusion often arises when certain categories within the dataset are too similar, causing misclassification of certain samples. This paper proposes an …

Dual-Feature Attention-Based Contrastive Prototypical Clustering for Multimodal Remote Sensing Data

2024 · IEEE Transactions on Geoscience and Remote Sensing

The integrated use of multisource remote sensing (RS) data in Earth observation missions has garnered considerable attention. Hyperspectral images (HSIs) offer extensive spatial and spectral detail, whereas light detection and ranging (LiDAR) data provide elevation …

Research Progress of Knowledge Graph and Attention Mechanism in Recommender Systems

2025

With the development of the Internet and the explosive expansion of information volume, it becomes arduous for users to make a choice in the face of overwhelming information. This makes the recommendation system an effective …