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Social Networks (SNs) have attracted many users and have become an integrated a part of the individual’s daily practices. The rapid climb of SNs like Twitter and Facebook has generated great deal of knowledge that sets direction for research in social relationships. The knowledge network represented by Facebook is predicated on information transmission, sharing, and exchange. The prediction process from prior information of the event helps to know the evolution of social network and assists the companies in effective decisions making during a typical recommendation system. Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations. Link prediction is a crucial research direction within the field of complex networks and data processing. Some complex physical processes like local stochastic process also are wont to measure the similarity between network nodes and improve the accuracy of the link prediction. In other words two linked nodes during a network may have a possible relationship.
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Link Prediction in Social Network Using Artificial Neural Network
Editore:
LAP Lambert Academic Publishing, 2022
ISBN 10: 6200095221
ISBN 13: 9786200095220
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Da: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Social Networks (SNs) have attracted many users and have become an integrated a part of the individual s daily practices. The rapid climb of SNs like Twitter and Facebook has generated great deal of knowledge that sets direction for research in social relat. Codice articolo 693919631
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Link Prediction in Social Network Using Artificial Neural Network
Editore:
LAP LAMBERT Academic Publishing Jul 2022, 2022
ISBN 10: 6200095221
ISBN 13: 9786200095220
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Social Networks (SNs) have attracted many users and have become an integrated a part of the individual's daily practices. The rapid climb of SNs like Twitter and Facebook has generated great deal of knowledge that sets direction for research in social relationships. The knowledge network represented by Facebook is predicated on information transmission, sharing, and exchange. The prediction process from prior information of the event helps to know the evolution of social network and assists the companies in effective decisions making during a typical recommendation system. Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations. Link prediction is a crucial research direction within the field of complex networks and data processing. Some complex physical processes like local stochastic process also are wont to measure the similarity between network nodes and improve the accuracy of the link prediction. In other words two linked nodes during a network may have a possible relationship. 60 pp. Englisch. Codice articolo 9786200095220
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Link Prediction in Social Network Using Artificial Neural Network
Editore:
LAP LAMBERT Academic Publishing Jul 2022, 2022
ISBN 10: 6200095221
ISBN 13: 9786200095220
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Neuware -Social Networks (SNs) have attracted many users and have become an integrated a part of the individual¿s daily practices. The rapid climb of SNs like Twitter and Facebook has generated great deal of knowledge that sets direction for research in social relationships. The knowledge network represented by Facebook is predicated on information transmission, sharing, and exchange. The prediction process from prior information of the event helps to know the evolution of social network and assists the companies in effective decisions making during a typical recommendation system. Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations. Link prediction is a crucial research direction within the field of complex networks and data processing. Some complex physical processes like local stochastic process also are wont to measure the similarity between network nodes and improve the accuracy of the link prediction. In other words two linked nodes during a network may have a possible relationship.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch. Codice articolo 9786200095220
Quantità: 2 disponibili
Immagini fornite dal venditore
Link Prediction in Social Network Using Artificial Neural Network
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200095221
ISBN 13: 9786200095220
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Social Networks (SNs) have attracted many users and have become an integrated a part of the individual's daily practices. The rapid climb of SNs like Twitter and Facebook has generated great deal of knowledge that sets direction for research in social relationships. The knowledge network represented by Facebook is predicated on information transmission, sharing, and exchange. The prediction process from prior information of the event helps to know the evolution of social network and assists the companies in effective decisions making during a typical recommendation system. Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations. Link prediction is a crucial research direction within the field of complex networks and data processing. Some complex physical processes like local stochastic process also are wont to measure the similarity between network nodes and improve the accuracy of the link prediction. In other words two linked nodes during a network may have a possible relationship. Codice articolo 9786200095220
Quantità: 1 disponibili