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Integrating label propagation with graph convolutional networks for recommendation
Currently, graph convolutional networks (GCN) have achieved significant progress in recommender systems, due to its remarkable capability on...
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Counter Propagation Network Based Extreme Learning Machine
The extreme learning machine (ELM), a new learning algorithm for single hidden layer feedforward neural networks (SLFN), has drawn interest of a...
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GNPA: a hybrid model for social influence maximization in dynamic networks
With the growing size of online social communities, influence propagation in social networks has become a hot topic of the research. Most of the...
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BPSL: a new rumor source location algorithm based on the time-stamp back propagation in social networks
Finding a rumor source is a major issue in the analysis of social networks. In this problem, the rumor source is usually estimated from a given...
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A hybrid phase-field isogeometric analysis to crack propagation in porous functionally graded structures
Porosities exist as pores of different sizes within a structure to fabricate lightweight materials and the sintering process. The porous structure...
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Scholar Influence Maximization via Opinion Leader and Graph Embedding Regression in Social Networks
The significance of influential nodes in information diffusion within scholar social networks has attracted increasing attention in the field of...
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Temporally consistent video colorization with deep feature propagation and self-regularization learning
Video colorization is a challenging and highly ill-posed problem. Although recent years have witnessed remarkable progress in single image...
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A Bi-objective Source Hiding Method for Network Propagation
In many scenarios, sources want to publish information anonymously and allow it to be distributed on a large scale in a short period of time. To this...
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Influence Maximization in Dynamic Networks Using Reinforcement Learning
Influence maximization (IM) has been widely studied in recent decades, aiming to maximize the spread of influence over networks. Despite many works...
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Experimental Study on Low Frequency Time-Code Timing Signal Propagation in Forest Environment
AbstractForest environment is a common complex scene in the application of radio time service. When the timing signal enters the fo rest, signal...
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Influence maximization based on community structure and second-hop neighborhoods
With the spread of Internet and big data research and applications, influence propagation in networks becomes one of the hot topics in the field of...
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Reducing power grid cascading failure propagation by minimizing algebraic connectivity in edge addition
Analyzing network robustness under various circumstances is generally regarded as a challenging problem. Robustness against failure is one of the...
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Overlap** Community Discovery Algorithm Based on Three-Level Neighbor Node Influence
In view of the high time complexity of the current overlap** community discovery algorithm and the low stability, an overlap** community...
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Backward Propagation Algorithm
In Chapter 6 , we have systematically introduced the basic neural network algorithm: starting from the...
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Underwater stereo-matching algorithm based on belief propagation
Using stereo-imaging systems to collect 3D information is innovative and flexible for underwater exploration. The stereo-matching of underwater image...
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Influence maximization on temporal networks: a review
Influence maximization (IM) is an important topic in network science where a small seed set is chosen to maximize the spread of influence on a...
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Asymmetric Centrality Game Against Network Epidemic Propagation
The Mirai botnet network epidemic discovered in 2016 falls into the category of numerous epidemics propagated by attackers over a network to gain...
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Storyline Generation from News Articles Based on Approximate Personalized Propagation of Neural Predictions
Generating a storyline is aiming to discover the evolution of events from news websites. Some existing approaches aim to automatically cluster news...
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A Sample Reuse Strategy for Dynamic Influence Maximization Problem
Dynamic influence maximization problem (DIMP) aims to maintain a group of influential users within an evolving social network to maximize the...
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What Factors Can Facilitate Efficient Propagation of Chinese Neologisms–A Corpus-Driven Study with Internet Usage Data
With the development of information technologies, our world currently faces such an overwhelming mass of neologisms. Therefore, the study of...