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[交流] 中科院1区计算机期刊IPM【IF:7.4, 免版面费】专刊征稿—从文本提取地理信息

期刊名: Information Processing and Management
简称:IPM
中科院JCR分区:计算机科学 - 1区
CCF等级:数据库/数据挖掘/内容检索下B类
影响因子:7.4
审稿周期:平均两月
费用: 免版面费
专刊官网:  https://www.sciencedirect.com/jo ... sing-and-management

Geographic Information Extraction from Texts
Vast and ever-increasing amounts of semi- and unstructured text data, including social media posts, website texts, and historical archives, are available online and offline. These documents often refer to geographic regions or specific places and contain valuable but textually encoded geographic information in the form of toponyms, place names, and location descriptions. The information is useful not only for scientific studies, such as spatial humanities, but can also for various practical applications, such as disaster management and disease surveillance. Scientists from many fields have an increased interest in researching and applying methods to infer the geographical focus of documents or to extract geographic references from unstructured and heterogeneous texts and then resolve these references unambiguously to places or spaces on the Earth’s surface. Despite the encouraging progress in geographic information extraction, there are still many unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. With the special issue, we aim to foster discussion and exchange of recent advances in different aspects of geographic information extraction from texts. The special issue will provide an opportunity for the authors of the First GeoExT Workshop (to be held at the 45th European Conference on Information Retrieval in Dublin) to extend their research papers published in the workshop proceedings. Furthermore, this issue is open to other researchers working on the topics covered by the event.

Possible topics of submission:
Document geocoding
Toponym recognition and resolution
Toponym matching
Method generalizability (regions, languages, data sources)
Multi-source data (e.g., text and image) fusion for method improvement
Tweets geolocating at hyper-local levels
Location description extraction and resolution
Relation extraction and disambiguation
Fine-grained toponym resolution
Historical toponym resolution
Historical archive geovisualization
Gazetteer enrichment for resolving ancient and evolving toponyms
Dataset annotation for approach training and evaluation
Platforms and metrics for approach evaluation
Framework or service to support solution customizing
Standards or unified interfaces for system development
Novel applications of geographic information in texts
Analyzing and processing geotagged social media
Location privacy protection for online users

Important dates:
Submissions close: 1 September 2023

Guest editors:
Dr. Xuke Hu, German Aerospace Center, Jena, Germany
Prof. Ross Purves, Department of Geography, University of Zurich, Zurich, Switzerland
Assoc. Prof. Bernd Resch, Department of Geoinformatics, University of Salzburg, Salzburg, Austria
Dr. Jens Kersten, Institute of Data Science, German Aerospace Center, Jena, Germany
Assoc. Prof. Kristin Stock, School of Mathematical and Computational Sciences, Massey University, Auckland, New Zealand

Contact:
Dr. Xuke Hu, email: xuke.hu@dlr.de, wechat: w134571654
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2楼2023-02-14 20:43:33
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3楼2023-02-18 17:22:32
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