Spatio-Temporal Information Extraction and Geoparsing for Public Chinese Resumes
ISPRS International Journal of Geo-Information, 2023 As an important carrier of individual information, the resume is an important data source for studying the spatio-temporal evolutionary characteristics of individual and group behaviors.
Tan Yongbin, Wu Zhang
exaly +4 more sources
Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text
Remote Sensing, 2020 The automatic extraction of geospatial information is an important aspect of data mining. Computer systems capable of discovering geographic information from natural language involve a complex process called geoparsing, which includes two important tasks:
Edwin Aldana-Bobadilla +2 more
exaly +4 more sources
Geo-Semantic-Parsing: AI-Powered Geoparsing by Traversing Semantic Knowledge Graphs [PDF]
Decision Support Systems, 2020 Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus preventing its exploitation in real-time applications.
Maurizio Tesconi +2 more
exaly +2 more sources
A pragmatic guide to geoparsing evaluation [PDF]
Lang Resour Eval, 2018 Empirical methods in geoparsing have thus far lacked a standard evaluation framework describing the task, metrics and data used to compare state-of-the-art systems. Evaluation is further made inconsistent, even unrepresentative of real world usage by the
Milan Gritta +2 more
semanticscholar +2 more sources
Twitter-Based Flood Damage Mapping Using Text Classification and Geoparsing Techniques [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesSocial media is a prominent source of real-time information for disaster understanding. This study provides a method that uses natural language processing (NLP), machine learning, and geoparsing for flood damage mapping and classification from Twitter ...
Z. Amirgholizadeh +2 more
doaj +2 more sources
Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing
AGILE: GIScience Series, 2022 . Geoparsing, the task of extracting toponyms from texts and associating them with geographic locations, has witnessed remarkable progress over the past years.
Ling Cai, Gengchen Mai, Meilin Shi
exaly +2 more sources
Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation [PDF]
Sensors, 2019 In recent years, Online Social Networks (OSNs) have received a great deal of attention for their potential use in the spatial and temporal modeling of events owing to the information that can be extracted from these platforms. Within this context, one of
Aldo Hernandez-Suarez +6 more
doaj +2 more sources
Religions, 2022 This project uses local sources to visualize and analyze the spatial distribution of Buddhist sites in Hangzhou 杭州, China, in the Southern Song dynasty (1127–1279).
Jeffrey Liu, Ziling Wan
doaj +2 more sources
Applying machine learning and geolocation techniques to social media data (Twitter) to develop a resource for urban planning. [PDF]
PLoS ONE, 2021 With all the recent attention focused on big data, it is easy to overlook that basic vital statistics remain difficult to obtain in most of the world.
Sveta Milusheva +5 more
doaj +2 more sources
Geo-parsing and analysis of road traffic crash incidents for data-driven emergency response planning [PDF]
HeliyonRoad traffic crashes (RTCs) are a major public health concern worldwide, particularly in Nigeria, where road transport is the most common mode of transportation.
Patricia Ojonoka Idakwo +3 more
doaj +2 more sources