Li Guo

FraudNE: a Joint Embedding Approach for Fraud Detection

2018

Detecting fraudsters is a meaningful problem for both users and e-commerce platform. Existing graph-based approaches mainly adopt shallow models, which cannot capture the highly non-linear relationship between vertexes in a bipartite graph composed of users …

Towards Aggregated Features: A Novel Proxy Detection Method Using NetFlow Data

2020

Proxies can provide privacy and anonymity protection for users, but can also be exploited by attackers to hide their malicious behaviors. In order to strengthen the monitoring and management of network, proxy detection has become …

Abnormal Sound Detection of Electrical Equipment Based on Time-Spectrum Information Fusion

2023

In the daily monitoring and maintenance of electrical equipment, the detection of abnormal sound is a very important part, and the high accuracy and efficiency of sound to distinguish the abnormal state of the equipment …

QuantNAS: Quantization-aware Neural Architecture Search For Efficient Deployment On Mobile Device

2024

Deep convolutional networks are increasingly applied in mobile AI scenarios. To achieve efficient deployment, researchers combine neural architecture search (NAS) and quantization to find the best quantized architecture. However, existing methods overlook the on-device implementation …

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 …

Knowledge Graph Embedding: A Survey of Approaches and Applications

2017 · IEEE Transactions on Knowledge and Data Engineering

Knowledge graph (KG) embedding is to embed components of a KG including entities and relations into continuous vector spaces, so as to simplify the manipulation while preserving the inherent structure of the KG. It can …

Social Recommendation with an Essential Preference Space

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Social recommendation, which aims to exploit social information to improve the quality of a recommender system, has attracted an increasing amount of attention in recent years. A large portion of existing social recommendation models are …

DAN: Deep Attention Neural Network for News Recommendation

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

With the rapid information explosion of news, making personalized news recommendation for users becomes an increasingly challenging problem. Many existing recommendation methods that regard the recommendation procedure as the static process, have achieved better recommendation …