Technical Information

Page, John S.

doi:10.1016/b978-088415228-6.50166-0

Cited by 18 publications

(19 citation statements)

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“…The PageRank algorithm was initially implemented in Google's search engine [7]. In PageRank, node's importance can be interpreted as the more a node is pointed by important nodes, the more it is important.…”

Section: Pagerankmentioning

confidence: 99%

Generalization in human pathfinding as a stochastic navigation process on Wikipedia

Ficzere

Hollósi

Frankó

et al. 2023

Preprint

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Models of human navigation have been investigated in many ways on complex networks. These findings suggest that the characteristics of human navigation change during navigation from the start to the destination. Nonetheless, the degree to which navigation is influenced by the human navigator versus the graph and environment remains somewhat unclear. Our study focuses on the initial stage of human navigation, investigating the influence of the graph structure on navigation through the use of a PageRank-based random walk model. We investigate the PageRank model with the classical uniform and also power-law position based transition probabilities. Our results indicate that a significant proportion of early generalization phase navigation can be simulated with random navigation.

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Section: Pagerankmentioning

confidence: 99%

Generalization in human pathfinding as a stochastic navigation process on Wikipedia

Ficzere

Hollósi

Frankó

et al. 2023

Preprint

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“…MonitorRank [11] uses the historical and current time-series metrics, along with the call graph of the service-based system to build an unsupervised model for ranking. This technique identifies metrics correlated to system anomalies by using an adaptation of the PageRank algorithm [69]. Farshchi et al [21] adopts regression-based analysis to find the correlation between operation's activity logs and the operation activity's effect on cloud resources.…”

Section: Related Workmentioning

confidence: 99%

DeLag: Using Multi-Objective Optimization to Enhance the Detection of Latency Degradation Patterns in Service-Based Systems

Traini

Cortellessa

2023

IIEEE Trans. Software Eng.

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Performance debugging in production is a fundamental activity in modern service-based systems. The diagnosis of performance issues is often time-consuming, since it requires thorough inspection of large volumes of traces and performance indices. In this paper we present DeLag, a novel automated search-based approach for diagnosing performance issues in service-based systems. DeLag identifies subsets of requests that show, in the combination of their Remote Procedure Call execution times, symptoms of potentially relevant performance issues. We call such symptoms Latency Degradation Patterns. DeLag simultaneously searches for multiple latency degradation patterns while optimizing precision, recall and latency dissimilarity. Experimentation on 700 datasets of requests generated from two microservice-based systems shows that our approach provides better and more stable effectiveness than three state-of-the-art approaches and general purpose machine learning clustering algorithms. DeLag is more effective than all baseline techniques in at least one case study (with p ≤ 0.05 and non-negligible effect size). Moreover, DeLag outperforms in terms of efficiency the second and the third most effective baseline techniques on the largest datasets used in our evaluation (up to 22%).

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“…where α can be seen as a decay factor, and β as a vector of initial centralities (source ranks), scaled by α. We take this definition from [Franceschet, 2021], which gives a slightly simplified and generalized version of the original definition from [Page et al, 1999].…”

Section: Spectral Centralitiesmentioning

confidence: 99%

Network Modelling Methods for Precision Medicine

Nushi

Popescu

Martin

et al. 2022

Systems Biology Modelling and Analysis

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Technical Information

Cited by 18 publications

References 0 publications

Generalization in human pathfinding as a stochastic navigation process on Wikipedia

Generalization in human pathfinding as a stochastic navigation process on Wikipedia

DeLag: Using Multi-Objective Optimization to Enhance the Detection of Latency Degradation Patterns in Service-Based Systems

Network Modelling Methods for Precision Medicine

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