Network analysis of inter-organizational success factor relationships
Conference proceedings article
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Publication Details
Author list: Kongburan W., Padungweang P., Krathu W., Chan J.
Publisher: Hindawi
Publication year: 2017
Volume number: Part F130152
Start page: 83
End page: 84
Number of pages: 2
ISBN: 9781450352925
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
Abstract
One of the best ways to deal with the problem of knowledge distillation in unstructured text is applying text mining. This machine learning-based approach can provide extracted useful information from large body of texts, in a reasonable time. However, the results are usually in complicated forms, which meant it is a non-trivial task in term of interpretation. In this paper, we present appropriate visualizations and analyses in order to tackle the tangled network representing relationship between entities (i.e. terms extracted from raw text). Conducted on a case study of information extraction in the business management domain, our results reveal the hidden relationships of inter-organizational success factors in a simple structured way. These results can assist companies to understand and generate business strategies, in terms of the collaboration aspect. ฉ 2017 ACM.
Keywords
Circle graph, Inter-organizational relationships, Network analysis, Organic graph, Success factor