Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/34120
Title: Network mining: Applications to business data
Authors: Kumara, Soundar R.
Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0001-8054-5606
Çavdur, Fatih
AAG-9471-2021
8419687000
Keywords: Algorithms
Stock market
Business systems
Networks
Financial systems
Network mining
Algorithms
Networks (circuits)
Finance
Business networks
Business organizations
Highly-correlated
Business relationships
Graph construction
Business systems
Financial system
Industry
Computer Science
Dynamic asset trees
Food webs
Financial networks
Markets
Graphs
Issue Date: Jul-2014
Publisher: Springer
Citation: Çavdur, F. ve Kumara, S. R. (2014). "Network mining: Applications to business data". Information Systems Frontiers, 16(3), 473-490.
Abstract: This research addresses the problem of analyzing the temporal dynamics of business organizations. In particular, we concentrate on inferring the related businesses, i.e., are there groups of companies that are highly correlated through some measurement (metric)? We argue that business relationships derived from general literature (i.e., newspaper articles, news items etc.) may help us create a network of related companies (business networks). On the other hand, relative movement of stock prices can give us an indication of related companies (asset graphs). We also expect to see some relationships between these two kinds of networks. We adapt the asset graph construction approach from the literature for our asset graph implementations, and then, define our methodology for business network construction. Finally, an introduction to the exploration of some relationships between the asset graphs and business networks is presented.
URI: https://doi.org/10.1007/s10796-012-9355-z
https://link.springer.com/article/10.1007/s10796-012-9355-z
http://hdl.handle.net/11452/34120
ISSN: 1387-3326
1572-9419
Appears in Collections:Scopus
Web of Science

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