Titlebook: ;

BANAL

Understanding Ethereum Transactions via Network Approach,of Ethereum transaction records remains under-explored. In this chapter, we model Ethereum transaction records as a complex network and further study the problem of phishing detection and transaction tracking via node classification and link prediction, respectively, which provides a deeper understa

弓箭

Find Your Meal Pal: A Case Study on Yelp Network, photos. Along with the social relationships between users, Yelp enables a recommendation engine to make precise restaurants recommendations, which improves the user experience of the website and promote the revenues of restaurants. In this chapter, we focus on the Yelp friend network to make friend

GRIPE

乳白光

Time Series Classification Based on Complex Network,ication, human activity recognition and radio signal modulation identification. At present, some promising methods have been proposed to transform time series classification into graph classification by mapping time series to graphs. However, these transformation methods with fixed mapping rules may

Irritate

Exploring the Controlled Experiment by Social Bots,ts, on the one hand, serve human beings, on the other hand, cause the pollution of the network environment. Therefore, more and more researches begin to focus on social bots. In this chapter, we first introduce the concept of social bots, including the definition, application and influence. Then we

本土

Information Source Estimation with Multi-Channel Graph Neural Network,tures of two channels are aggregated together to estimate the probability of each node to be the source node. We evaluate our method on both synthetic and real-world networks. Extensive experiments demonstrate the effectiveness of our method on the task of identifying the information source.

ALTER

antidepressant

CEDE

聚集

Understanding Ethereum Transactions via Network Approach,ing models and compare our proposed method with these embedding technologies on realistic Ethereum transaction records. Experimental results demonstrate the superiority of our TBW in learning more informative representations, and is essential for Ethereum network analysis.