Network mining: Applications to business data

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)473-490
Number of pages18
JournalInformation Systems Frontiers
Volume16
Issue number3
DOIs
StatePublished - Jan 1 2014

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Network mining: Applications to business data'. Together they form a unique fingerprint.

Cite this