Hongwei Wang
13 papers in the PaperMetrix corpus
Papers by this author
-
Knowledge Graph Convolutional Networks for Recommender Systems
2019
To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information. In general, the …
-
Structural Alignment based Zero-shot Classification for Remote Sensing Scenes
2018
Zero-shot classification aims to classify unseen classes instances without any training data. However, the problem of class structure in consistency between visual space and semantic space severely affects zero-shot classification performance for remote sensing scenes. …
-
A Heuristic Algorithm for Optimal Service Composition in Complex Manufacturing Networks
2019 · Complexity
Service composition in a Cloud Manufacturing environment involves the adaptive and optimal assembly of manufacturing services to achieve quick responses to varied manufacturing needs. It is challenged by the inherent heterogeneity and complexity of these …
-
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
2019 · arXiv (Cornell University)
Knowledge graphs capture structured information and relations between a set of entities or items. As such knowledge graphs represent an attractive source of information that could help improve recommender systems. However, existing approaches in this …
-
Security of railway control systems: A survey, research issues and challenges
2022 · High-speed Railway
With the rapid development of railway transportation, higher requirements for capacity are increasing and amount of communication, computer and control technologies are applied in train control systems which is the popular method for train control. …
-
Generating User-Engaging News Headlines
2023
Pengshan Cai, Kaiqiang Song, Sangwoo Cho, Hongwei Wang, Xiaoyang Wang, Hong Yu, Fei Liu, Dong Yu. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.
-
Retrieval Augmented Instruction Tuning for Open NER with Large Language Models
2024 · arXiv (Cornell University)
The strong capability of large language models (LLMs) has been applied to information extraction (IE) through either retrieval augmented prompting or instruction tuning (IT). However, the best way to incorporate information with LLMs for IE …
-
Class Incremental Fault Diagnosis under Limited Fault Data via Supervised Contrastive Knowledge Distillation
2025 · arXiv (Cornell University)
Class-incremental fault diagnosis requires a model to adapt to new fault classes while retaining previous knowledge. However, limited research exists for imbalanced and long-tailed data. Extracting discriminative features from few-shot fault data is challenging, and …
-
DKN: Deep Knowledge-Aware Network for News Recommendation
2018 · arXiv (Cornell University)
Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense. However, existing methods …
-
RippleNet
2018
To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph …
-
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
2019
Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems. In this …
-
Exploring High-Order User Preference on the Knowledge Graph for Recommender Systems
2019 · ACM Transactions on Information Systems
To address the sparsity and cold-start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve the performance of recommendation. In this article, we consider …
-
DKN
2018
Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense. However, existing methods …