Pub Date : 2023-01-25DOI: 10.1007/s10707-023-00488-3
Wenwen Li, Sizhe Wang, S. Arundel, Chia-Yu Hsu
{"title":"Correction to: GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning","authors":"Wenwen Li, Sizhe Wang, S. Arundel, Chia-Yu Hsu","doi":"10.1007/s10707-023-00488-3","DOIUrl":"https://doi.org/10.1007/s10707-023-00488-3","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42334787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-16DOI: 10.1007/s10707-023-00486-5
Senlin Mu, Xiao Huang, Moyang Wang, Di Zhang, Dong Xu, Xiang Li
{"title":"Optimizing pedestrian simulation based on expert trajectory guidance and deep reinforcement learning","authors":"Senlin Mu, Xiao Huang, Moyang Wang, Di Zhang, Dong Xu, Xiang Li","doi":"10.1007/s10707-023-00486-5","DOIUrl":"https://doi.org/10.1007/s10707-023-00486-5","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47614783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1007/s10707-022-00469-y
Ling Cai, Krzysztof Janowicz, Rui Zhu, Gengchen Mai, Bo Yan, Zhangyu Wang
Qualitative spatial/temporal reasoning (QSR/QTR) plays a key role in research on human cognition, e.g., as it relates to navigation, as well as in work on robotics and artificial intelligence. Although previous work has mainly focused on various spatial and temporal calculi, more recently representation learning techniques such as embedding have been applied to reasoning and inference tasks such as query answering and knowledge base completion. These subsymbolic and learnable representations are well suited for handling noise and efficiency problems that plagued prior work. However, applying embedding techniques to spatial and temporal reasoning has received little attention to date. In this paper, we explore two research questions: (1) How do embedding-based methods perform empirically compared to traditional reasoning methods on QSR/QTR problems? (2) If the embedding-based methods are better, what causes this superiority? In order to answer these questions, we first propose a hyperbolic embedding model, called HyperQuaternionE, to capture varying properties of relations (such as symmetry and anti-symmetry), to learn inversion relations and relation compositions (i.e., composition tables), and to model hierarchical structures over entities induced by transitive relations. We conduct various experiments on two synthetic datasets to demonstrate the advantages of our proposed embedding-based method against existing embedding models as well as traditional reasoners with respect to entity inference and relation inference. Additionally, our qualitative analysis reveals that our method is able to learn conceptual neighborhoods implicitly. We conclude that the success of our method is attributed to its ability to model composition tables and learn conceptual neighbors, which are among the core building blocks of QSR/QTR.
{"title":"HyperQuaternionE: A hyperbolic embedding model for qualitative spatial and temporal reasoning.","authors":"Ling Cai, Krzysztof Janowicz, Rui Zhu, Gengchen Mai, Bo Yan, Zhangyu Wang","doi":"10.1007/s10707-022-00469-y","DOIUrl":"https://doi.org/10.1007/s10707-022-00469-y","url":null,"abstract":"<p><p>Qualitative spatial/temporal reasoning (QSR/QTR) plays a key role in research on human cognition, e.g., as it relates to navigation, as well as in work on robotics and artificial intelligence. Although previous work has mainly focused on various spatial and temporal calculi, more recently representation learning techniques such as embedding have been applied to reasoning and inference tasks such as query answering and knowledge base completion. These subsymbolic and learnable representations are well suited for handling noise and efficiency problems that plagued prior work. However, applying embedding techniques to spatial and temporal reasoning has received little attention to date. In this paper, we explore two research questions: (1) How do embedding-based methods perform empirically compared to traditional reasoning methods on QSR/QTR problems? (2) If the embedding-based methods are better, what causes this superiority? In order to answer these questions, we first propose a hyperbolic embedding model, called HyperQuaternionE, to capture varying properties of relations (such as symmetry and anti-symmetry), to learn inversion relations and relation compositions (i.e., composition tables), and to model hierarchical structures over entities induced by transitive relations. We conduct various experiments on two synthetic datasets to demonstrate the advantages of our proposed embedding-based method against existing embedding models as well as traditional reasoners with respect to entity inference and relation inference. Additionally, our qualitative analysis reveals that our method is able to learn conceptual neighborhoods implicitly. We conclude that the success of our method is attributed to its ability to model composition tables and learn conceptual neighbors, which are among the core building blocks of QSR/QTR.</p>","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9554233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-18DOI: 10.1007/s10707-022-00474-1
Xinya Lei, Weijing Song, R. Fan, Ruyi Feng, Lizhe Wang
{"title":"Semi-supervised geological disasters named entity recognition using few labeled data","authors":"Xinya Lei, Weijing Song, R. Fan, Ruyi Feng, Lizhe Wang","doi":"10.1007/s10707-022-00474-1","DOIUrl":"https://doi.org/10.1007/s10707-022-00474-1","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47134091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-17DOI: 10.1007/s10707-022-00480-3
Yanbing Bai, Jinhua Su, Yulong Zou, B. Adriano
{"title":"Knowledge distillation based lightweight building damage assessment using satellite imagery of natural disasters","authors":"Yanbing Bai, Jinhua Su, Yulong Zou, B. Adriano","doi":"10.1007/s10707-022-00480-3","DOIUrl":"https://doi.org/10.1007/s10707-022-00480-3","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42619952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1007/s10707-022-00483-0
M. Sakr, Cyril Ray, C. Renso
{"title":"Big mobility data analytics: recent advances and open problems","authors":"M. Sakr, Cyril Ray, C. Renso","doi":"10.1007/s10707-022-00483-0","DOIUrl":"https://doi.org/10.1007/s10707-022-00483-0","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49042605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-29DOI: 10.1007/s10707-022-00481-2
Gengchen Mai, C. Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, K. Janowicz, Stefano Ermon, Ni Lao
{"title":"Towards general-purpose representation learning of polygonal geometries","authors":"Gengchen Mai, C. Jiang, Weiwei Sun, Rui Zhu, Yao Xuan, Ling Cai, K. Janowicz, Stefano Ermon, Ni Lao","doi":"10.1007/s10707-022-00481-2","DOIUrl":"https://doi.org/10.1007/s10707-022-00481-2","url":null,"abstract":"","PeriodicalId":55109,"journal":{"name":"Geoinformatica","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43005108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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