Direct geocoding of street intersections in text message analysis tasks

Article Properties
Abstract
Cite
Lopushanskiy, Alexandr, and Yana Bekeneva. “Direct Geocoding of Street Intersections in Text Message Analysis Tasks”. E3S Web of Conferences, vol. 471, 2024, p. 04020, https://doi.org/10.1051/e3sconf/202447104020.
Lopushanskiy, A., & Bekeneva, Y. (2024). Direct geocoding of street intersections in text message analysis tasks. E3S Web of Conferences, 471, 04020. https://doi.org/10.1051/e3sconf/202447104020
Lopushanskiy A, Bekeneva Y. Direct geocoding of street intersections in text message analysis tasks. E3S Web of Conferences. 2024;471:04020.
Journal Category
Geography
Anthropology
Recreation
Environmental sciences
Refrences
Title Journal Journal Categories Citations Publication Date
Detection and prediction of traffic accidents using deep learning techniques Cluster Computing
  • Science: Science (General): Cybernetics: Information theory
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
10 2023
Mining Social Networks to Detect Traffic Incidents Information Systems Frontiers
  • Science: Science (General): Cybernetics: Information theory
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
13 2021
Improving a Street-Based Geocoding Algorithm Using Machine Learning Techniques

Applied Sciences
  • Technology: Engineering (General). Civil engineering (General)
  • Science: Biology (General)
  • Science: Physics
  • Science: Chemistry
  • Science: Chemistry: General. Including alchemy
  • Technology: Engineering (General). Civil engineering (General)
  • Science: Chemistry
  • Science: Physics
  • Technology: Technology (General): Industrial engineering. Management engineering
  • Technology: Chemical technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
  • Technology: Engineering (General). Civil engineering (General)
9 2020
From Twitter to detector: Real-time traffic incident detection using social media data Transportation Research Part C: Emerging Technologies
  • Technology: Engineering (General). Civil engineering (General): Transportation engineering
  • Technology: Engineering (General). Civil engineering (General)
  • Technology: Engineering (General). Civil engineering (General)
175 2016
10.1016/S0198-9715(98)00034-9 Computers, Environment and Urban Systems
  • Geography. Anthropology. Recreation: Environmental sciences
  • Geography. Anthropology. Recreation
  • Geography. Anthropology. Recreation: Human ecology. Anthropogeography: Settlements: Cities. Urban geography
  • Social Sciences: Communities. Classes. Races: Urban groups. The city. Urban sociology
  • Geography. Anthropology. Recreation: Environmental sciences
  • Social Sciences
1998
Refrences Analysis
The category Technology: Engineering (General). Civil engineering (General) 5 is the most frequently represented among the references in this article. It primarily includes studies from Applied Sciences and Computers, Environment and Urban Systems. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year