Zhao Li

Multi-Swarm Particle Swarm Optimization Co-Evolution Algorithm based on Principal Component Analysis for Solving Conditional Nonlinear Optimal Perturbation

2015 · Advances in computer science research

Conditional nonlinear optimal perturbation (CNOP) is an initial perturbation evolving into the largest nonlinear evolution at the prediction time. It has played an important role in predictability and sensitivity studies of nonlinear numerical models. Generally, …

Campus Network Security Defense Strategy

2017

This paper analyzes the characteristics of campus network and focuses on the key issues of campus network security prevention. The prevention strategies are analyzed from intranet security monitoring, network operation and other aspects, and the …

Detecting Crowdturfing "Add to Favorites" Activities in Online Shopping

2018

"Add to Favorites" is a popular function in online shopping sites which helps users to make a record of potentially interesting items for future purchases. It is usually regarded as a type of explicit feedback …

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, …

Attention with Long-Term Interval-Based Deep Sequential Learning for Recommendation

2020 · Complexity

Modeling user behaviors as sequential learning provides key advantages in predicting future user actions, such as predicting the next product to purchase or the next song to listen to, for the purpose of personalized search …

Research on Classification and Recognition of Emotional EEG Signal Based on Extreme Learning Machine

2021 · 2021 IEEE 5th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)

There are many research methods of emotion recognition, and the emotion recognition of EEG signals is one of the important researches in the field of emotion computing. Extreme learning machine can recognize more generalized features …

A Trusted Privacy-Preserving Model for Cross-Chain Transactions Based on zk_SNARKs

2023

Currently, the privacy protection technology of blockchain is not mature enough, such as user data leakage and lack of anonymity exist, and these problems are especially serious when conducting cross-chain transactions. In this paper, we …

Large Language Model Enhanced Knowledge Representation Learning: A Survey

2024 · arXiv (Cornell University)

Knowledge Representation Learning (KRL) is crucial for enabling applications of symbolic knowledge from Knowledge Graphs (KGs) to downstream tasks by projecting knowledge facts into vector spaces. Despite their effectiveness in modeling KG structural information, KRL …

Reinforcement Learning for Relation Classification from Noisy Data

2018 · arXiv (Cornell University)

Existing relation classification methods that rely on distant supervision assume that a bag of sentences mentioning an entity pair are all describing a relation for the entity pair. Such methods, performing classification at the bag …

Hierarchical Bipartite Graph Neural Networks: Towards Large-Scale E-commerce Applications

2020

The e-commerce appeals to a multitude of online shoppers by providing personalized experiences and becomes indispensable in our daily life. Accurately predicting user preference and making a recommendation of favorable items plays a crucial role …

Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs

2020

Knowledge graphs have been widely adopted to improve recommendation accuracy. The multi-hop user-item connections on knowledge graphs also endow reasoning about why an item is recommended. However, reasoning on paths is a complex combinatorial optimization …