187 citations · 302 across the 5 of their papers we have counts for
5 papers
Conflating point of interest (POI) data: A systematic review of matching methods
Kai Sun, Yingjie Hu, Yue Ma +2
Point of interest (POI) data provide digital representations of places in the real world, and have been increasingly used to understand human-place interactions, support urban mana…
Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages
Yingjie Hu, Gengchen Mai, Chris Cundy +6
Social media messages posted by people during natural disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many…
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…
TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT
Bing Zhou, Lei Zou, Yingjie Hu +2
Extracting precise geographical information from textual contents is crucial in a plethora of applications. For example, during hazardous events, a robust and unbiased toponym extr…
Location reference recognition from texts: A survey and comparison
Xuke Hu, Zhiyong Zhou, Hao Li +5
A vast amount of location information exists in unstructured texts, such as social media posts, news stories, scientific articles, web pages, travel blogs, and historical archives.…