Mining Logomaps for Ecosystem Intelligence

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dc.contributor.authorBasole, Rahul
dc.date.accessioned2020-12-24T19:11:54Z
dc.date.available2020-12-24T19:11:54Z
dc.date.issued2021-01-05
dc.description.abstractEcosystem 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.131
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70743
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData, Text and Web Mining for Business Analytics
dc.subjectecosystem intelligence
dc.subjectgraph modeling
dc.subjectimage recognition
dc.subjectlogomaps
dc.subjectvisualization
dc.titleMining Logomaps for Ecosystem Intelligence
prism.startingpage1081

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