Titlebook: Knowledge and Systems Sciences; 22nd International S Jian Chen,Van-Nam Huynh,Jiangning Wu Conference proceedings 2023 The Editor(s) (if app

開始發(fā)作

LinkEE: Linked List Based Event Extraction with?Attention Mechanism for?Overlapping Events information. Bi-directional feature information of the input is learned through Bi-LSTM, while contextual information is captured by Hydra attention to enhance the text vector representation. Experimental results on the public dataset FewFC illustrate that the proposed model LinkEE is superior to previous methods.

MARS

1865-0929 he 20 full papers included in this volume were carefully reviewed and selected from 56 submissions. The volume is divided in topical sections that cover the following topics: data mining and machine learning,?complex systems modeling, decision analysis and knowledge management,?opinion mining and kn

Lethargic

aggrieve

A Hybrid Supervised Learning Approach for?Intrusion Detection Systemslgorithms. This framework integrates decision trees (DT), random forests (RF), extra trees (ET), and extreme gradient boosting (XGBoost) methods to identify network attacks. Through experimental evaluation on the Edge-IIoTset dataset, the system demonstrates solid performance by effectively and accu

Pantry

土產(chǎn)

做事過頭

Chinese Medicinal Materials Price Index Trend Prediction Using GA-XGBoost Feature Selection and?Bidised model obtained more superior prediction compared to the state-of-the-art methods, and specialized in predicting long-term goal (90 days). Results also show the weather and air quality data can improve the prediction performance.

感情脆弱

不愿

Research on?the?Behavioral Characteristics and?Performance Influence Factors of?Venture Capitalists mpetition, the positive impact or insignificant impact of Resource Limitation, Resource Adequacy, Resource Uniqueness, Industry Diversity and Regional Diversity on investment performance gradually turns negative.

全面

Social Capital, Market Motivation and Knowledge Sharing: A Multiplex Network Perspective on Blockchaial capital on knowledge-sharing behavior. The research findings enrich the understanding of the factors that influence users’ knowledge-sharing behavior and provide important insights for how BKC can effectively incentivize users to make sustained contributions.