Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
4-1-2021 12:00 AM
End Date
9-1-2021 12:00 AM
Description
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.
Mining Logomaps for Ecosystem Intelligence
Online
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.
https://aisel.aisnet.org/hicss-54/da/data_text_web_mining/5