This review presents a comprehensive exploration of hybrid and ensemble deep learning
models within Natural Language Processing (NLP), shedding light on their transformative …

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 …

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 …

The use of social media and location-based networks through GPS-enabled devices
provides geospatial data for a plethora of applications in urban studies. However, the extent …

Address parsing is a crucial task in natural language processing, particularly for Chinese
addresses. The complex structure and semantic features of Chinese addresses present …

In the Australian construction industry, effective supply chain risk management (SCRM) is
critical due to its complex networks and susceptibility to various risks. This study explores the …

Observed regional variation in geotagged social media text is often attributed to dialects,
where features in language are assumed to exhibit region-specific properties. While dialects …

Automatically extracting geographic information from text is the key to harnessing the vast
amount of spatial knowledge that only exists in this unstructured form. The fundamental …

Geoparsers aim to find place names in unstructured texts and locate them geographically.
This process produces georeferenced data usable for spatial analyses or visualisations …

This paper explores cognitive place associations; conceptualised as a place‐based mental
model that derives subconscious links between geographic locations. Utilising a large …