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  • Search: subject:"Graph convolutional network"
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Year of publication
Subject
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Graph theory 3 Graphentheorie 3 Business network 2 Graph convolutional network 2 Network 2 Netzwerk 2 Regional cluster 2 Regionales Cluster 2 Unternehmensnetzwerk 2 Bergbau 1 Betriebliche Standortwahl 1 Cluster analysis 1 Clusteranalyse 1 Clustering 1 Co-location pattern mining 1 Community identification 1 Data Mining 1 Data mining 1 Descriptive statistics 1 Deskriptive Statistik 1 Firm location choice 1 Forecasting model 1 Gastronomie 1 Geldmarkt 1 Graph networks 1 Interbank market 1 Interbankenmarkt 1 Location selection 1 Location theory 1 Mining 1 Money market 1 Node embedding 1 Node2vec 1 Prognoseverfahren 1 Restaurant industry 1 Social network 1 Soziales Netzwerk 1 Standorttheorie 1 Transformative marketing 1 graph convolutional network 1
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Online availability
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Free 3 CC license 2
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 3 Aufsatz in Zeitschrift 3
Language
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English 3
Author
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Bhattacharya, Riju 1 Chen, Linlin 1 Gupta, Shivam 1 Han, Shuihua 1 Nagwani, Naresh Kumar 1 Sivarajah, Uthayasankar 1 Su, Zhaopei 1 Tripathi, Sarsij 1 Zhang, Haici 1
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Published in...
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Decision analytics journal 1 International Journal of Financial Studies : open access journal 1 Journal of business research : JBR 1
Source
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ECONIS (ZBW) 3
Showing 1 - 3 of 3
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Identifying a good business location using prescriptive analytics : restaurant location recommendation based on spatial data mining
Han, Shuihua; Chen, Linlin; Su, Zhaopei; Gupta, Shivam; … - In: Journal of business research : JBR 179 (2024), pp. 1-13
Persistent link: https://www.econbiz.de/10014555892
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A community detection model using node embedding approach and graph convolutional network with clustering technique
Bhattacharya, Riju; Nagwani, Naresh Kumar; Tripathi, Sarsij - In: Decision analytics journal 9 (2023), pp. 1-11
expanding field of study that has attracted much attention recently. Inspired by the graph convolutional network (GCN) approach … graph convolutional network. The weighted average matrix and scaled normalized matrices of low-dimensional vertices have ….39%, 98.79%, and 97.67% for Karate, Cora, CiteSeer, Facebook, and DBLP datasets, respectively. Thus, graph convolutional …
Persistent link: https://www.econbiz.de/10014533204
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A deep learning approach to dynamic interbank network link prediction
Zhang, Haici - In: International Journal of Financial Studies : open … 10 (2022) 3, pp. 1-16
temporal trading relationship prediction. There are two important components of the model, which are the Graph convolutional … network (GCN) and the Long short-term memory (LSTM) model. The GCN and LSTM components together capture the spatial …
Persistent link: https://www.econbiz.de/10013368354
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