Search results for "CheiRank"

showing 5 items of 5 documents

2019

We consider the network of 5 416 537 articles of English Wikipedia extracted in 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases with the top PageRank diseases being Tuberculosis, HIV/AIDS, and Malaria. From the reduced Google matrix, we determine the sensitivity of world countries to specific diseases integrating th…

CheiRank0303 health sciencesInformation retrievalGeneral Computer ScienceGoogle matrixComputer sciencebusiness.industryGeneral Engineering01 natural sciences3. Good healthlaw.invention03 medical and health sciencesPageRanklaw0103 physical sciencesGlobal networkEncyclopediaGeneral Materials ScienceThe Internet010306 general physicsbusiness030304 developmental biologyNetwork analysisIEEE Access
researchProduct

World Influence of Infectious Diseases from Wikipedia Network Analysis

2019

AbstractWe consider the network of 5 416 537 articles of English Wikipedia extracted in 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases with the top PageRank diseases being Tuberculosis, HIV/AIDS and Malaria. From the reduced Google matrix we determine the sensitivity of world countries to specific diseases integrat…

CheiRankComputer scienceHuman immunodeficiency virus (HIV)medicine.disease_cause01 natural sciences[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]law.invention03 medical and health sciencesPageRanklaw0103 physical sciencesGlobal networkmedicine010306 general physics030304 developmental biology0303 health sciencesInformation retrievalGoogle matrixMarkov processes[PHYS.PHYS.PHYS-SOC-PH]Physics [physics]/Physics [physics]/Physics and Society [physics.soc-ph]complex networksdata mining[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]ranking (statistics)3. Good healthInfectious diseaseslcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:TK1-9971Network analysisWikipedia
researchProduct

Contagion in Bitcoin Networks

2019

12 pages, 6 figures. Paper accepted in 2nd Workshop on Blockchain and Smart Contract Technologies (BSCT 2019), workshop satellite of 22nd International Conference on Business Information Systems (BIS 2019); International audience; We construct the Google matrices of bitcoin transactions for all year quarters during the period of January 11, 2009 till April 10, 2013. During the last quarters the network size contains about 6 million users (nodes) with about 150 million transactions. From PageRank and CheiRank probabilities, analogous to trade import and export, we determine the dimensionless trade balance of each user and model the contagion propagation on the network assuming that a user go…

CheiRankGoogle matrixMarkov chain[QFIN]Quantitative Finance [q-fin]Financial networksComputer science[PHYS.PHYS.PHYS-SOC-PH]Physics [physics]/Physics [physics]/Physics and Society [physics.soc-ph]Balance of trade01 natural sciences010305 fluids & plasmaslaw.inventionPageRankBankruptcylaw0103 physical sciencesHouse of cardsEconometrics010306 general physics[QFIN.TR]Quantitative Finance [q-fin]/Trading and Market Microstructure [q-fin.TR]ComputingMilieux_MISCELLANEOUS
researchProduct

Novel Version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network Using Social Impact

2020

International audience; Nowadays, information describing navigation behaviour of internet users are used in several fields, e-commerce, economy, sociology and data science. Such information can be extracted from different knowledge bases, including business-oriented ones. In this paper, we propose a new model for the PageRank, CheiRank and 2DRank algorithm based on the use of clickstream and pageviews data in the google matrix construction. We used data from Wikipedia and analysed links between over 20 million articles from 11 language editions. We extracted over 1.4 billion source-destination pairs of articles from SQL dumps and more than 700 million pairs from XML dumps. Additionally, we …

CheiRankPageRankSQLComputer sciencecomputer.internet_protocol01 natural sciences[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]010305 fluids & plasmaslaw.inventionCheiRankPageRanklaw0103 physical sciencesCentrality measures010306 general physicsClickstreamcomputer.programming_languageInformation retrievalGoogle matrixGoogle matrixPageviewsSocial impactPage viewcomputerClickstreamXMLWikipedia
researchProduct

Google matrix analysis of worldwide football mercato

2018

[EN] The worldwide football transfer market is analyzed as a directed complex network: the football clubs are the network nodes and the directed edges are weighted by the total amount of money transferred from a club to another. The Google matrix description allows to treat every club independently of their richness and allows to measure for a given club the efficiency of player sales and player acquisitions. The PageRank algorithm, developed initially for the World Wide Web, naturally characterizes the ability of a club to import players. The CheiRank algorithm, also developed to analyze large scale directed complex networks, characterizes the ability of a club to export players. The analy…

PageRankCheiRankComputer scienceBig dataComplex networksPLSFootballlaw.inventionWorld Wide WebBig dataCheiRankPageRanklawInternet dataQCAGoogle matrixMarkov chainsGoogle matrixMarkov chainbusiness.industryWeb dataComputingMilieux_PERSONALCOMPUTINGConferenceComplex networkFootball transfer marketSEMbusinessProceedings of the 2nd International Conference on Advanced Research Methods and Analytics (CARMA 2018)
researchProduct