Automatic extraction and geographization of urban traffic event based on natural Chinese text data
Information on real-time traffic events is necessary for many applications. With the rapid advancement of Internet, text published from network platforms has become an important data source for urban road traffic events. However, due to the complexity of massive multi-source web text and the diversi...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2453618 |
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| _version_ | 1832590883936010240 |
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| author | Chenyu Hu Hangbin Wu Chaoxu Wei Qianqian Chen Han Yue Wei Huang Chun Liu Ting Fu Junhua Wang |
| author_facet | Chenyu Hu Hangbin Wu Chaoxu Wei Qianqian Chen Han Yue Wei Huang Chun Liu Ting Fu Junhua Wang |
| author_sort | Chenyu Hu |
| collection | DOAJ |
| description | Information on real-time traffic events is necessary for many applications. With the rapid advancement of Internet, text published from network platforms has become an important data source for urban road traffic events. However, due to the complexity of massive multi-source web text and the diversity of spatial scenes in traffic events, existing methods are not enough to support accurate extraction and geographization of events from text, resulting in the information not being efficiently utilized. Therefore, in this study, we proposed a framework from the perspective of traffic events. First, the text is preprocessed, while road-related information is summarized. Next, a step-wise method for automatically extracting is proposed. Finally, we adopt methods for entity disambiguation and spatial computing. A case study of Shanghai is conducted, and the results show that our method is effective, which can make traffic events more complete and accurate in extraction, more multi-dimensional and fine-grained in geographization. |
| format | Article |
| id | doaj-art-5e7025a4bdd5498abbc92717ffd1605e |
| institution | Kabale University |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-5e7025a4bdd5498abbc92717ffd1605e2025-01-23T06:49:52ZengTaylor & Francis GroupGeocarto International1010-60491752-07622025-12-0140110.1080/10106049.2025.2453618Automatic extraction and geographization of urban traffic event based on natural Chinese text dataChenyu Hu0Hangbin Wu1Chaoxu Wei2Qianqian Chen3Han Yue4Wei Huang5Chun Liu6Ting Fu7Junhua Wang8Urban Mobility Institute, Tongji University, Shanghai, ChinaUrban Mobility Institute, Tongji University, Shanghai, ChinaCollege of Surveying and Geo-informatics, Tongji University, Shanghai, ChinaCollege of Surveying and Geo-informatics, Tongji University, Shanghai, ChinaCollege of Surveying and Geo-informatics, Tongji University, Shanghai, ChinaUrban Mobility Institute, Tongji University, Shanghai, ChinaUrban Mobility Institute, Tongji University, Shanghai, ChinaCollege of Transportation Engineering, Tongji University, Shanghai, ChinaCollege of Transportation Engineering, Tongji University, Shanghai, ChinaInformation on real-time traffic events is necessary for many applications. With the rapid advancement of Internet, text published from network platforms has become an important data source for urban road traffic events. However, due to the complexity of massive multi-source web text and the diversity of spatial scenes in traffic events, existing methods are not enough to support accurate extraction and geographization of events from text, resulting in the information not being efficiently utilized. Therefore, in this study, we proposed a framework from the perspective of traffic events. First, the text is preprocessed, while road-related information is summarized. Next, a step-wise method for automatically extracting is proposed. Finally, we adopt methods for entity disambiguation and spatial computing. A case study of Shanghai is conducted, and the results show that our method is effective, which can make traffic events more complete and accurate in extraction, more multi-dimensional and fine-grained in geographization.https://www.tandfonline.com/doi/10.1080/10106049.2025.2453618Traffic eventChinese web textcrowd-sourced datainformation extraction and geographization |
| spellingShingle | Chenyu Hu Hangbin Wu Chaoxu Wei Qianqian Chen Han Yue Wei Huang Chun Liu Ting Fu Junhua Wang Automatic extraction and geographization of urban traffic event based on natural Chinese text data Geocarto International Traffic event Chinese web text crowd-sourced data information extraction and geographization |
| title | Automatic extraction and geographization of urban traffic event based on natural Chinese text data |
| title_full | Automatic extraction and geographization of urban traffic event based on natural Chinese text data |
| title_fullStr | Automatic extraction and geographization of urban traffic event based on natural Chinese text data |
| title_full_unstemmed | Automatic extraction and geographization of urban traffic event based on natural Chinese text data |
| title_short | Automatic extraction and geographization of urban traffic event based on natural Chinese text data |
| title_sort | automatic extraction and geographization of urban traffic event based on natural chinese text data |
| topic | Traffic event Chinese web text crowd-sourced data information extraction and geographization |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2025.2453618 |
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