Results 141 to 150 of about 1,844,514 (182)

The Rising Importance of Distributional Barriers to the Adoption of Climate Change Mitigation Policies

Montfort S, Fesenfeld L, Ingold K, Repke T, Callaghan M.   +4 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

ChineseTR: A weakly supervised toponym recognition architecture based on automatic training data generator and deep neural network

Trans. GIS, 2022
Toponym recognition is used to extract toponyms from natural language texts, which is a fundamental task of ubiquitous geographic information applications.
Qinjun Qiu, Zhong Xie, Shu Wang, Yunqiang Zhu, Hairong Lv, Kai Sun   +5 more
semanticscholar   +1 more source

NeuroTPR: A neuro‐net toponym recognition model for extracting locations from social media messages

Trans. GIS, 2020
Social media messages, such as tweets, are frequently used by people during natural disasters to share real‐time information and to report incidents. Within these messages, geographic locations are often described. Accurate recognition and geolocation of
Jimin Wang, Yingjie Hu, K. Joseph
semanticscholar   +1 more source

Locating the Ancient Toponym of “Kindāu”: The Recognition of an Indo-European God in the Assyrian Inscriptions of the Seventh Century BC

Iran, 2020
“Kindāu” is the name of an ancient fortress located in the west of Iran, which has been mentioned three times in the inscriptions of the Assyrian king, Sargon II.
Iraj Rezaie
semanticscholar   +1 more source

Deep Learning for Chinese Toponym Recognition: A BiLSTM-CRF Based Approach

International Conference Civil Engineering and Architecture
Chinese toponym recognition faces significant challenges due to linguistic complexity and diverse naming patterns. While existing studies rely on rule-based or statistical models, these approaches suffer from manual feature engineering and poor ...
Peng Ye, Wu Xiao, Yadi Wang
semanticscholar   +1 more source

BiC2V-NFLAT: Chinese toponym recognition based on Bi-Char2Vec and non-flat-lattice transformer

International Conference on Internet of Things and Smart City
In response to the issues of missing context semantics and imbalanced datasets in Chinese toponym recognition tasks, this paper proposes a Chinese toponym recognition method based on Bi-Char2Vec and Non-Flat-Lattice Transformer.
Manzhen Yang
semanticscholar   +1 more source

Toponym Extraction in Thai Tweets Using a Hybrid Approach

International Conferences on Intelligent Information Technology, 2020
Crowdsourcing has become an important tool in areas such as business and marketing. It can help organizations solve large-scale problems in areas including traffic management and political campaigning.
Manassanan Boonnavasin, Prapaporn Rattanatamrong   +1 more
semanticscholar   +1 more source

Named Entity Recognition Among Chinese MicroBlog Based on Cascaded CRF

International Conferences on Audio, Language and Image Processing, 2018
There are several features in the content of microblog, including brief, flexible, too colloquial, too much noise caused by informality terms (abbreviations, cyber words), etc. These features are new challenges for named entity recognition. In this paper,
Yixue Xing, Yonghua Zhu, Ke Zhang, Shenkai Liu, Jin Zhou   +4 more
semanticscholar   +1 more source

Is AI-Based Toponym extraction of street-level imagery a reliable approach for validating OpenStreetMap Toponyms?

Boletim de Ciências Geodésicas
: Toponyms play a crucial role in the identification and singularisation of geographic features. While traditional sources include gazetteers, official records, and historical maps, collaborative mapping platforms such as OpenStreetMap (OSM) offer a ...
D. Nunes, S. Camboim
semanticscholar   +1 more source

Correctness Comparison of ChatGPT‐4, Gemini, Claude‐3, and Copilot for Spatial Tasks

Trans. GIS
Generative AI including large language models (LLMs) has recently gained significant interest in the geoscience community through its versatile task‐solving capabilities including programming, arithmetic reasoning, generation of sample data, time‐series ...
H. Hochmair, L. Juhász, Takoda Kemp
semanticscholar   +1 more source