Link prediction is a core data analysis issue in the field of network science and data mining. Previous link prediction methods mainly focus on how to accurately identify those potential links. In practice, it is also...
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Link prediction is a core data analysis issue in the field of network science and data mining. Previous link prediction methods mainly focus on how to accurately identify those potential links. In practice, it is also very critical to understand the decision-making process, i.e., explaining why there is a link between two nodes. Unfortunately, how to predict links in an explainable manner for general graphs still remains unaddressed. To fill this gap, we make an attempt towards this direction by introducing an interpretable link prediction method based on sparse decision tree. Our method first extracts explainable features that are highly relevant to the target link. Subsequently, it constructs a concise decision tree by either imposing depth constraint on classic algorithms or employing recent algorithms for constructing optimal sparse decision tree. Experimental results on real networks demonstrate that our method not only provides a transparent decision process for link prediction but also delivers performance comparable to many classic methods. The source codes of our method are publicly available at: https://***/Hailu-Tan/Interpretable-Link-Prediction.
In recent years,magneto-electro-elastic(MEE)cylindrical shells with step-wise thicknesses have shown significant potential in the field of vibration energy *** aid the design of such energy harvesting devices,an accur...
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In recent years,magneto-electro-elastic(MEE)cylindrical shells with step-wise thicknesses have shown significant potential in the field of vibration energy *** aid the design of such energy harvesting devices,an accurate free vibration analysis of embedded MEE cylindrical shells with step-wise thicknesses is performed within the framework of symplectic *** using the Legendre transformation,a new known vector is defined to transform the higher-order partial differential governing equations into a set of lower-order ordinary differential ***,the original vibration analysis is regarded as an eigen problem in the symplectic space,and analytical solutions can be represented by the symplectic *** numerical examples,the new analytical solutions are compared with the existing results,and good agreement is ***,the effects of critical design parameters on free vibration characteristics are thoroughly *** numerical results can serve as benchmarks for the development of other approximate or numerical methods.
By applying the fish swarm algorithm to the generation of the multicast tree under the dynamic satellite network, a method for generating the multicast tree with good adaptability and inheritance was found, and the ge...
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Coincidence detection of two curves or two surfaces has wide application in computer-aided design(CAD)and computer-aided geometric design(CAGD).Proper reparameterization is the most complicated part in the *** paper p...
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Coincidence detection of two curves or two surfaces has wide application in computer-aided design(CAD)and computer-aided geometric design(CAGD).Proper reparameterization is the most complicated part in the *** paper presents and proves the efficient and necessary coincidence condition for two rational Bézier curves in a new *** also proposes an effective and efficient proper reparameterization method,Algorithm 1,for detecting a rational Bézier curve which can be degenerated into a new one of a lower degree.A numerical proper reparameterization method,Algorithm 2,and examples are also *** 1 is up to ten times faster than other prevailing methods,and Algorithm 2 is twice as fast and half as close as other prevailing *** CAD systems using Algorithm 1 and Algorithm 2 will hold accuracy and little computation time.
Music source separation isolates or separates the desired accompaniment or singing voice from the song recording. This study solves this problem in the time domain using only one channel. Music contains rich informati...
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Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtua...
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Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtual reality,mobile devices,and smart *** general,these IoT applications always bring higher energy consumption than traditional applications,which are usually *** provide persistent energy,many references have studied the offloading problem to save energy ***,the dynamic environment dramatically increases the optimization difficulty of the offloading *** this paper,we aim to minimize the energy consumption of the entireMECsystemunder the latency constraint by fully considering the dynamic *** games,we propose amulti-agent deep reinforcement learning approach based on the bi-level actorcritic learning structure to jointly optimize the offloading decision and resource allocation,which can solve the combinatorial optimization problem using an asymmetric method and compute the Stackelberg equilibrium as a better convergence point than Nash equilibrium in terms of Pareto *** method can better adapt to a dynamic environment during the data transmission than the single-agent strategy and can effectively tackle the coordination problem in the multi-agent *** simulation results show that the proposed method could decrease the total computational overhead by 17.8%compared to the actor-critic-based method and reduce the total computational overhead by 31.3%,36.5%,and 44.7%compared with randomoffloading,all local execution,and all offloading execution,respectively.
Advances in automated essay scoring (AES) have traditionally relied on labeled essays, requiring tremendous cost and expertise for their acquisition. Recently, large language models (LLMs) have achieved great success ...
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Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based softw...
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Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based software engineering have undergone fundamental changes where the network plays an increasingly important *** this context,it is required to develop new methodologies as well as technical tools for network-based knowledge representation,knowledge services and knowledge ***,the term“network”has different meanings in different ***,some breakthroughs in several bottleneck problems of complex networks promote the developments of the new methodologies and technical tools for network-based knowledge representation,knowledge services and knowledge *** paper first reviews some recent advances on complex networks,and then,in conjunction with knowledge graph,proposes a framework of networked knowledge which models knowledge and its relationships with the perspective of complex *** the unique advantages of deep learning in acquiring and processing knowledge,this paper reviews its development and emphasizes the role that it played in the development of knowledge ***,some challenges and further trends are discussed.
In the past few years, latency-sensitive task computing over the industrial internet of things (IIoT) has played a key role in an increasing number of intelligent applications, such as intelligent self-driving vehicle...
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Missing values exist widely in real-world datasets, which restrict the performance of data mining. In this paper, we propose a joint optimization framework to mine attribute associations and category structures in inc...
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