Connecting Patterns Inspire Link Prediction in Complex Networks

Abstract

Link prediction uses observed data to predict future or potential relations in complex networks. An underlying hypothesis is that two nodes have a high likelihood of connecting together if they share many common characteristics. The key issue is to develop different similarity-evaluating approaches. However, in this paper, by characterizing the differences of the similarity scores of existing and nonexisting links, we find an interesting phenomenon that two nodes with some particular low similarity scores also have a high probability to connect together. Thus, we put forward a new framework that utilizes an optimal one-variable function to adjust the similarity scores of two nodes. Theoretical analysis suggests that more links of low similarity scores (long-range links) could be predicted correctly by our method without losing accuracy. Experiments in real networks reveal that our framework not only enhances the precision significantly but also predicts more long-range links than state-of-the-art methods, which deepens our understanding of the structure of complex networks.

Convergence and Inequality in Research Globalization

“…This measurement weakness, often exacerbated by the research reward system [13], has led to schemes of "gaming the system" where abusive behaviors, such as citation cartels [19,39] and coercive citations [29,56,24], have become an ever more concerning issue for research integrity and assessments. Research into better measurements of impact have been active [20,6,61,32,50,3], though widely accepted alternatives have yet to emerge.…”

Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

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“…By establishing a braking energy recovery storage system in an electric vehicle, it can meet the two requirements when it recharges the energy, which is the requirement of large current and high power [5,6]. For the problem of short driving range with pure electric vehicles, braking energy recovery technology can improve its endurance [7][8][9][10]. In the braking process, the motor is controlled as a generator in the state of power generation, converts part of the entire vehicle's kinetic energy into electrical energy, and ultimately returns it to be stored in a battery pack or a super capacitor [11,12].…”

W-Index: An Index for Evaluating Link Prediction considering Only the Role of Wins

“…Being able to effectively and efficiently predict unobserved links will allow us to mine future interactions among members in the social network [2,3], conduct successful recommendation in useritem bipartite networks [4,5], provide guidance for the planning process of infrastructure systems [6], optimize asset allocation in the stock market [7], discover drug-target interactions or identify targeting drugs for new targetcandidate proteins [8,9], and save costs and reduce operational risks for manufacturing companies [10,11]. Up to the present, various methods have been proposed for link prediction [12][13][14][15][16], most of which can be classified with heuristic-based approaches and learning-based approaches [17]. However, there are many long-standing challenges in the evaluation of link prediction methods.…”