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Research on the evolution and driving factors of the coupling relationship among tourism industry, urbanization and human settlements of the urban agglomeration in the middle reaches of the Yangtze River. [PDF]

PLoS One
Yang Y, Xie A, Zhou X, Cheng K.
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Toponymic fieldwork and related office processing: federal and provincial perspectives. V. Recognition of the names of unincorporated urban communities: the state of the art in Ontario, 1979

, 1979
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Materiality of Memorialization: Mapping Migrant Women's Landmarks in Europe. [PDF]

Open Res Eur
Miyamoto B, Ojala-Fulwood M, Čapská V, Bakas FE, Lyman I, Barros-Del Río MA, Bostenaru Dan M, Comino A, Frigren P, Konstantinova V, Martins H, Prosinger L, Räsänen P, Ristovska-Josifovska B, Ruiz M.   +14 more
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Neural Network Approaches to Medical Toponym Recognition

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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
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Toponym recognition on Turkish tweets

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In recent years, Twitter has become a popular platform for following and spreading trends, news and ideas all over the world. Geographical scope of tweets is crucial to many tasks like disaster management, event tracking and information retrieval. First step for assigning a geographical location to a tweet is toponym recognition.
Kezban Dilek Onal, Pinar Karagoz, Ruket Cakici   +2 more
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ChineseTR: A weakly supervised toponym recognition architecture based on automatic training data generator and deep neural network

Transactions in GIS, 2022
AbstractToponym recognition is used to extract toponyms from natural language texts, which is a fundamental task of ubiquitous geographic information applications. Existing toponym recognition methods with state‐of‐the‐art performance mainly leverage supervised learning (i.e., deep‐learning‐based approaches) with parameters learned from massive ...
Qinjun Qiu, Zhong Xie, Shu Wang, Yunqiang Zhu, Hairong Lv, Kai Sun   +5 more
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NeuroTPR: A neuro‐net toponym recognition model for extracting locations from social media messages

Transactions in GIS, 2020
AbstractSocial 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 these locations are critical for reaching those in need.
Jimin Wang, Yingjie Hu, Kenneth Joseph
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