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Exploring Geo-Text Data with Machine Learning Models for Knowledge Discovery Online
Recent years have witnessed an exponential growth of data that link geographic locations and textual descriptions (geo-text data for short). Examples include geotagged tweets, news articles containing place names, online neighborhood reviews, and many others. Meanwhile, the fast advancements of machine learning provide powerful tools enabling us to effectively analyze a large amount of geo-text data for knowledge discovery. In this presentation, I will present studies that discover knowledge by analyzing three types of geo-text data using various machine learning models and geospatial analysis methods. The discovered knowledge can support disaster response, urban planning, and other applications that benefit our society.
Presenter: Yingjie Hu, Department of Geography
See more DSSN Events
- Date:
- Tuesday, April 19, 2022
- Time:
- 2:00pm - 3:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Online:
- This is an online event. Event URL will be sent via registration email.
- Categories:
- Digital Scholarship
