Lihong Wang

Ordering-Based Kalman Filter Selective Ensemble for Classification

2020 · IEEE Access

This paper investigates Kalman Filter-based Heuristic Ensemble (KFHE), which is a new perspective on multi-class ensemble classification with performance significantly better or at least as good as the state-of-the-art algorithms. We prove that the sample …

Adaptive Attentional Network for Few-Shot Knowledge Graph Completion

2020

Few-shot Knowledge Graph (KG) completion is a focus of current research, where each task aims at querying unseen facts of a relation given its few-shot reference entity pairs. Recent attempts solve this problem by learning …

Research on Movie Recommendation Algorithm Based on Stack De-noising Auto-encoder

2021 · Journal of Physics Conference Series

Abstract Focused on the problems that the randomness of the noise-adding operation in the de-noising auto-encoder (DAE), and the data matrix does not consider the impact of trusted users on the deep preferences of target …

Development and Application of Data Processing Software for Geo-resistivity

2022

Observation and analysis of geo-resistivity is one of the important methods of earthquake prediction. Based on the geo-resistivity data observed by a seismic station in 2020, a data processing software is designed and developed. Based …

Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations

2021 · arXiv (Cornell University)

Event extraction is a fundamental task for natural language processing. Finding the roles of event arguments like event participants is essential for event extraction. However, doing so for real-life event descriptions is challenging because an …

Reinforcement Learning Guided Multi-Objective Exam Paper Generation

2023 · Society for Industrial and Applied Mathematics eBooks

To reduce the repetitive and complex work of instructors, exam paper generation (EPG) technique has become a salient topic in the intelligent education field, which targets at generating high-quality exam paper automatically according to instructor-specified …

Self-supervised Bipartite Graph Representation Learning: A Dirichlet Max-margin Matrix Factorization Approach

2024 · ACM Transactions on Intelligent Systems and Technology

Bipartite graph representation learning aims to obtain node embeddings by compressing sparse vectorized representations of interactions between two types of nodes, e.g., users and items. Incorporating structural attributes among homogeneous nodes, such as user communities, …

Semantically Smooth Knowledge Graph Embedding

2015

Shu Guo, Quan Wang, Bin Wang, Lihong Wang, Li Guo. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long …