Abstract
Ecosystem intelligence is typically based on highly structured data. More recently, we have seen a growth in extracting knowledge from unstructured textual data sources. Yet, one form of unstructured data has largely been ignored in ecosystem intelligence: image-based data. With an increased use of images and graphics in corporate presentations, social media posts, and annual reports, there is a greater need and opportunity to mine this potentially trapped knowledge. We introduce and describe a human-assisted knowledge discovery approach applied to one particular type of image-based data, namely logomaps, combining image recognition, graph modeling, and visualization to provide insights into business ecosystems. We demonstrate the logomap mining method through a case study of the emerging artificial intelligence (AI) ecosystem and conclude with a discussion of implications and future work.
Cite
CITATION STYLE
Basole, R. C. (2021). Mining logomaps for ecosystem intelligence. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2020-January, pp. 1081–1090). IEEE Computer Society. https://doi.org/10.24251/hicss.2021.131
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