{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T20:55:32Z","timestamp":1781729732851,"version":"3.54.5"},"reference-count":52,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T00:00:00Z","timestamp":1629763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41901315"],"award-info":[{"award-number":["41901315"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recognized that geocoding is challenging. Recent advances in deep learning have promoted the use of the neural network to improve the performance of geocoding. However, most of the existing approaches consider only the local context, e.g., neighboring words in a sentence, as opposed to the global context, e.g., the topic of the document. Lack of global information may have a severe impact on the robustness of the model. To fill the research gap, this paper proposes a novel global context embedding approach to generate linguistic and geospatial features through topic embedding and location embedding, respectively. A deep neural network called LGGeoCoder, which integrates local and global features, is developed to solve the geocoding as a classification problem. The experiments on a Wikipedia place name dataset demonstrate that LGGeoCoder achieves competitive performance compared with state-of-the-art models. Furthermore, the effect of introducing global linguistic and geospatial features in geocoding to alleviate the ambiguity and scarcity problem is discussed.<\/jats:p>","DOI":"10.3390\/ijgi10090572","type":"journal-article","created":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T04:43:43Z","timestamp":1629780223000},"page":"572","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["The Integration of Linguistic and Geospatial Features Using Global Context Embedding for Automated Text Geocoding"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2153-7483","authenticated-orcid":false,"given":"Zheren","family":"Yan","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5361-6034","authenticated-orcid":false,"given":"Can","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangcun","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianya","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1145\/2047296.2047297","article-title":"Geographic information retrieval","volume":"3","author":"Purves","year":"2011","journal-title":"SIGSPATIAL Spec."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1080\/15230406.2013.799738","article-title":"Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): A case study in 2012 US Presidential Election","volume":"40","author":"Tsou","year":"2013","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1080\/15230406.2019.1705187","article-title":"Delineating and modeling activity space using geotagged social media data","volume":"47","author":"Hu","year":"2020","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Campelo, C.E. (2015). Geographically-Aware Information Retrieval on the Web. Encyclopedia of Information Science and Technology, IGI Global. [3rd ed.].","DOI":"10.4018\/978-1-4666-5888-2.ch383"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1007\/s10579-017-9385-8","article-title":"What\u2019s missing in geographical parsing?","volume":"52","author":"Gritta","year":"2018","journal-title":"Lang. Resour. Eval."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/tgis.12212","article-title":"Automated geocoding of textual documents: A survey of current approaches","volume":"21","author":"Melo","year":"2017","journal-title":"Trans. GIS"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1080\/13658816.2018.1459627","article-title":"Using provenance to disambiguate locational references in social network posts","volume":"33","author":"Hervey","year":"2019","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1080\/13658816.2011.604636","article-title":"The convergence of GIS and social media: Challenges for GIScience","volume":"25","author":"Sui","year":"2011","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_9","unstructured":"Wick, M. (2018, July 03). Geonames. Available online: https:\/\/www.geonames.org\/."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"DeLozier, G., Baldridge, J., and London, L. (2015, January 25\u201330). Gazetteer-independent toponym resolution using geographic word profiles. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9531"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s10708-014-9553-y","article-title":"Using machine learning methods for disambiguating place references in textual documents","volume":"80","author":"Santos","year":"2015","journal-title":"GeoJournal"},{"key":"ref_12","unstructured":"Speriosu, M., and Baldridge, J. (2013, January 4\u20139). Text-driven toponym resolution using indirect supervision. Proceedings of the Annual Metting of the Association for Computational Linguistics, Sofia, Bulgaria."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1459352.1459355","article-title":"Word sense disambiguation: A survey","volume":"41","author":"Navigli","year":"2009","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gritta, M., Pilehvar, M., and Collier, N. (2018, January 15\u201320). Which melbourne? Augmenting geocoding with maps. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, Australia.","DOI":"10.18653\/v1\/P18-1119"},{"key":"ref_15","unstructured":"Devlin, J., Chang, M.W., Lee, K., and Toutanova, K. (2019, January 2\u20137). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Minneapolis, MN, USA."},{"key":"ref_16","first-page":"33","article-title":"From text to geographic coordinates: The current state of geocoding","volume":"19","author":"Goldberg","year":"2007","journal-title":"URISA J."},{"key":"ref_17","first-page":"37","article-title":"Geocoding location expressions in Twitter messages: A preference learning method","volume":"9","author":"Zhang","year":"2014","journal-title":"J. Spat. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3875","DOI":"10.1098\/rsta.2010.0149","article-title":"Use of the Edinburgh geoparser for georeferencing digitized historical collections","volume":"368","author":"Grover","year":"2010","journal-title":"Philos. Trans. R. Soc. A Math. Phys. Eng. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, Y., Chen, M., Lin, X., Yu, H., and Liu, Y. (2010, January 18\u201320). An evidence-based approach for toponym disambiguation. Proceedings of the 18th International Conference on Geoinformatics, Beijing, China.","DOI":"10.1109\/GEOINFORMATICS.2010.5567805"},{"key":"ref_20","unstructured":"Li, H., Srihari, R., Niu, C., and Li, W. (September, January 24). Location normalization for information extraction. Proceedings of the 19th International Conference on Computational Linguistics, Taipei, Taiwan."},{"key":"ref_21","unstructured":"Speriosu, M., Brown, T., Moon, T., Baldridge, J., and Erk, K. (2010, January 15). Connecting language and geography with region-topic models. Proceedings of the Workshop on Computational Models of Spatial Language Interpretation (COSLI), Portland, OR, USA."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1111\/tgis.12023","article-title":"Analyzing Relatedness by Toponym Co-O ccurrences on Web Pages","volume":"18","author":"Liu","year":"2014","journal-title":"Trans. GIS"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1080\/13658810701626236","article-title":"Using co-occurrence models for placename disambiguation","volume":"22","author":"Overell","year":"2008","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_24","unstructured":"Bishop, C. (2006). Pattern Recognition and Machine Learning, Springer."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wing, B., and Baldridge, J. (2014, January 25\u201329). Hierarchical discriminative classification for text-based geolocation. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar.","DOI":"10.3115\/v1\/D14-1039"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Melo, F., and Martins, B. (2015, January 26\u201327). Geocoding textual documents through the usage of hierarchical classifiers. Proceedings of the 9th Workshop on Geographic Information Retrieval, Paris, France.","DOI":"10.1145\/2837689.2837690"},{"key":"ref_27","unstructured":"Liu, J., and Inkpen, D. (June, January 31). Estimating user location in social media with stacked denoising auto-encoders. Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, Denver, CO, USA."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Murdock, V. (2014, January 11). Dynamic location models. Proceedings of the Thirty-Seventh International ACM SIGIR Conference on Research and Development in Information Retrieval, Queensland, Australia.","DOI":"10.1145\/2600428.2609552"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Hulden, M., Silfverberg, M., and Francom, J. (2015, January 25\u201330). Kernel density estimation for text-based geolocation. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9149"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Rahimi, A., Baldwin, T., and Cohn, T. (2017, January 9\u201311). Continuous Representation of Location for Geolocation and Lexical Dialectology Using Mixture Density Networks. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark.","DOI":"10.18653\/v1\/D17-1016"},{"key":"ref_31","unstructured":"Wang, S., and Manning, C. (2012, January 8\u201314). Baselines and bigrams: Simple, good sentiment and topic classification. Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers-Volume 2, Jeju Island, Korea."},{"key":"ref_32","first-page":"3111","article-title":"Distributed Representations of Words and Phrases and their Compositionality","volume":"26","author":"Mikolov","year":"2013","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Bamman, D., Dyer, C., and Smith, N.A. (2014, January 22\u201327). Distributed representations of geographically situated language. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Baltimore, MD, USA.","DOI":"10.3115\/v1\/P14-2134"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Kejriwal, M., and Szekely, P. (2017, January 21\u201325). Neural Embeddings for Populated Geonames Locations. Proceedings of the International Semantic Web Conference, Vienna, Austria.","DOI":"10.1007\/978-3-319-68204-4_14"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Liu, Y., Liu, Z., Chua, T., and Sun, M. (2015, January 25). Topical word embeddings. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA.","DOI":"10.1609\/aaai.v29i1.9522"},{"key":"ref_36","first-page":"411","article-title":"spacy 2: Natural language understanding with bloom embeddings","volume":"7","author":"Honnibal","year":"2017","journal-title":"Convolut. Neural Netw. Increm. Parsing"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"242","DOI":"10.2307\/2267409","article-title":"Systems of syntactic analysis","volume":"18","author":"Chomsky","year":"1953","journal-title":"J. Symb. Log."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., and Manning, C. (2014, January 25\u201329). Glove: Global vectors for word representation. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar.","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref_39","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Vu, T., Yang, H., Nguyen, V., Oh, A., and Kim, M. (2017, January 13\u201316). Multimodal learning using convolution neural network and Sparse Autoencoder. Proceedings of the IEEE International Conference on Big Data and Smart Computing (BigComp), Jeju Island, Korea.","DOI":"10.1109\/BIGCOMP.2017.7881683"},{"key":"ref_41","unstructured":"Mao, X.J., Shen, C., and Yang, Y.B. (2016, January 5\u201310). Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. Proceedings of the 30th International Conference on Neural Information Processing Systems, Barcelona, Spain."},{"key":"ref_42","first-page":"841","article-title":"On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes","volume":"14","author":"NG","year":"2002","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Weston, J., Ratle, F., Mobahi, H., and Collobert, R. (2012). Deep learning via semi-supervised embedding. Neural Networks: Tricks of the Trade, Springer.","DOI":"10.1007\/978-3-642-35289-8_34"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Lin, T., Goyal, P., Girshick, R., He, K., and Doll\u00e1r, P. (2017, January 22\u201329). Focal loss for dense object detection. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Michalski, R.S. (1983). A theory and methodology of inductive learning. Machine Learning, Elsevier.","DOI":"10.1016\/B978-0-08-051054-5.50008-X"},{"key":"ref_46","unstructured":"Phan, X., and Nguyen, C. (2018, July 03). GibbsLDA++: AC\/C++ Implementation of Latent Dirichlet Allocation, 2018. Git Code. Available online: https:\/\/github.com\/mrquincle\/gibbs-lda."},{"key":"ref_47","unstructured":"Zeiler, M.D. (2012). ADADELTA: An Adaptive Learning Rate Method. arXiv."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Kim, Y. (2014, January 25\u201329). Convolutional Neural Networks for Sentence Classification. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar.","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref_49","unstructured":"Kingma, D.P., and Ba, J. (2015). Adam: A Method for Stochastic Optimization. arXiv."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Li, R., Wang, S., Deng, H., Wang, R., and Chang, K.C.C. (2012, January 12\u201316). Towards social user profiling: Unified and discriminative influence model for inferring home locations. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, China.","DOI":"10.1145\/2339530.2339692"},{"key":"ref_51","unstructured":"Jurgens, D., Finethy, T., McCorriston, J., Xu, Y., and Ruths, D. (2015, January 26\u201329). Geolocation prediction in twitter using social networks: A critical analysis and review of current practice. Proceedings of the International AAAI Conference on Web and Social Media, Oxford, UK."},{"key":"ref_52","unstructured":"(2021, July 05). Wikipedia Contributors. \u2018Plagiarism\u2019, Wikipedia, The Free Encyclopedia. Available online: https:\/\/en.wikipedia.org\/wiki\/Dubai_Zoo."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/9\/572\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:50:15Z","timestamp":1760165415000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/9\/572"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,24]]},"references-count":52,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["ijgi10090572"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10090572","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,24]]}}}