{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:56:30Z","timestamp":1760241390636,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,7]],"date-time":"2018-02-07T00:00:00Z","timestamp":1517961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41171297, 41631177 & 41671393"],"award-info":[{"award-number":["41171297, 41631177 & 41671393"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Na\u00efve Geography, intelligent geographical information systems (GIS), and spatial data mining especially from social media all rely on natural-language spatial relations (NLSR) terms to incorporate commonsense spatial knowledge into conventional GIS and to enhance the semantic interoperability of spatial information in social media data. Yet, the inherent fuzziness of NLSR terms makes them challenging to interpret. This study proposes to interpret the fuzzy semantics of NLSR terms using the fuzzy random forest (FRF) algorithm. Based on a large number of fuzzy samples acquired by transforming a set of crisp samples with the random forest algorithm, two FRF models with different membership assembling strategies are trained to obtain the fuzzy interpretation of three line-region geometric representations using 69 NLSR terms. Experimental results demonstrate that the two FRF models achieve good accuracy in interpreting line-region geometric representations using fuzzy NLSR terms. In addition, fuzzy classification of FRF can interpret the fuzzy semantics of NLSR terms more fully than their crisp counterparts.<\/jats:p>","DOI":"10.3390\/ijgi7020058","type":"journal-article","created":{"date-parts":[[2018,2,7]],"date-time":"2018-02-07T12:20:29Z","timestamp":1518006029000},"page":"58","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Interpreting the Fuzzy Semantics of Natural-Language Spatial Relation Terms with the Fuzzy Random Forest Algorithm"],"prefix":"10.3390","volume":"7","author":[{"given":"Xiaonan","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shihong","family":"Du","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0410-714X","authenticated-orcid":false,"given":"Chen-Chieh","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Geography, National University of Singapore, Singapore 117570, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1851-016X","authenticated-orcid":false,"given":"Xueying","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9350-9126","authenticated-orcid":false,"given":"Xiuyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Frank, A.U., and Kuhn, W. (1995). Naive geography. Spatial Information Theory: A Theoretical Basis for GIS, Springer. Lecture Notes in Computer Sciences.","DOI":"10.1007\/3-540-60392-1"},{"key":"ref_2","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_3","unstructured":"Waugh, T.C., and Healey, R.G. (1994). Calibrating the meanings of spatial predicates from natural language: Line-region relations. Advances in GIS Research: Proceedings of the Sixth International Symposium on Spatial Data Handling, Department of Geography, University of Edinburgh."},{"key":"ref_4","first-page":"215","article-title":"Natural-language spatial relations between linear and areal objects: The topology and metric of English-language terms","volume":"12","author":"Shariff","year":"1998","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.compenvurbsys.2004.08.001","article-title":"Spatial queries with qualitative locations in spatial information systems","volume":"30","author":"Yao","year":"2006","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1080\/13658810600894323","article-title":"Formalizing natural-language spatial relations between linear objects with topological and metric properties","volume":"21","author":"Xu","year":"2007","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1080\/13658816.2016.1212356","article-title":"Classifying natural-language spatial relation terms with random forest algorithm","volume":"31","author":"Du","year":"2017","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_8","first-page":"29","article-title":"The fuzziness of English semantics","volume":"57","author":"Jin","year":"1988","journal-title":"Foreign Lang."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Egenhofer, M.J., and Herring, J.R. (1991). Categorizing Binary Topological Relations between Regions, Lines and Points in Geographic Databases, University of Maine. Technical Report.","DOI":"10.1007\/3-540-54414-3_36"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1023\/A:1009712514511","article-title":"Qualitative spatial representation and reasoning with the region connection calculus","volume":"1","author":"Cohn","year":"1997","journal-title":"Geoinformatica"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Petry, F.E., Robinson, V.B., and Cobb, M.A. (2005). Combined extraction of directional and topological relationship information from 2D concave objects. Fuzzy Modeling with Spatial Information for Geographic Problems, Springer.","DOI":"10.1007\/b138243"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1109\/TKDE.2006.102","article-title":"Modeling and computing ternary projective relations between regions","volume":"18","author":"Clementini","year":"2006","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","article-title":"Fuzzy sets","volume":"8","author":"Zadeh","year":"1965","journal-title":"Inf. Control"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/S0020-0255(71)80004-X","article-title":"Quantitative fuzzy semantics","volume":"3","author":"Zadeh","year":"1971","journal-title":"Inf. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"You, M., Filippi, A.M., G\u00fcneralp, \u0130., and G\u00fcneralp, B. (2017). What is the direction of land change? A new approach to land-change analysis. Remote Sens., 9.","DOI":"10.3390\/rs9080850"},{"key":"ref_16","unstructured":"Dev, S., Lee, Y.H., and Winkler, S. (arXiv, 2017). Systematic study of color space sand components for the segmentation of sky\/cloud images, arXiv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1080\/02693799008941546","article-title":"Fuzzy information representation and processing in conventional GIS software: Database design and application","volume":"4","author":"Wang","year":"1990","journal-title":"Int. J. Geogr. Inf. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1080\/02693799408901991","article-title":"Towards a natural language user interface: An approach of fuzzy query","volume":"8","author":"Wang","year":"1994","journal-title":"Int. J. Geogr. Inf. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1399","DOI":"10.1109\/TFUZZ.2014.2362121","article-title":"Indexing fuzzy spatiotemporal data for efficient querying: A meteorological application","volume":"23","author":"Sozer","year":"2015","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2851","DOI":"10.3233\/JIFS-169167","article-title":"Modeling and querying fuzzy spatiotemporal objects","volume":"31","author":"Cheng","year":"2016","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.3233\/JIFS-161616","article-title":"A fine fuzzy spatial partitioning model for line objects based on computing with words and application in natural language spatial query","volume":"32","author":"Guo","year":"2017","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_22","first-page":"1261","article-title":"Description of topological relations I: A unified fuzzy 9-intersection model","volume":"Volume 3612","author":"Wang","year":"2005","journal-title":"Advances in Natural Computation. ICNC 2005"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1080\/13658810600711345","article-title":"Computing the fuzzy topological relations of spatial objects based on induced fuzzy topology","volume":"20","author":"Liu","year":"2006","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ijar.2007.10.001","article-title":"Fuzzy region connection calculus: Representing vague topological information","volume":"48","author":"Schockaert","year":"2008","journal-title":"Int. J. Approx. Reason."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1016\/j.ijar.2011.07.001","article-title":"On standard models of fuzzy region connection calculus","volume":"52","author":"Liu","year":"2011","journal-title":"Int. J. Approx. Reason."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1080\/13658810110061162","article-title":"Nearness relations in environmental space","volume":"15","author":"Worboys","year":"2001","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1111\/j.1538-4632.2007.00700.x","article-title":"Neurofuzzy modeling of context\u2013contingent proximity relations","volume":"39","author":"Yao","year":"2007","journal-title":"Geogr. Anal."},{"key":"ref_28","unstructured":"Gertz, M., Huang, Y., Krumm, J., Sankaranarayanan, J., and Schneider, M. (2014, January 4\u20137). Modeling fuzzy topological predicates for fuzzy regions. Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Dallas, TX, USA."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ramossoto, A., Alonso, J.M., Reiter, E., Deemter, K.V., and Gatt, A. (arXiv, 2017). An empirical approach for modeling fuzzy geographical descriptors, arXiv.","DOI":"10.1109\/FUZZ-IEEE.2017.8015527"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/j.ijar.2010.02.003","article-title":"A fuzzy random forest","volume":"51","author":"Bonissone","year":"2010","journal-title":"Int. J. Approx. Reason."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/3477.658573","article-title":"Fuzzy decision trees: Issues and methods","volume":"28","author":"Janikow","year":"1988","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1007\/s00500-011-0778-0","article-title":"OFP_CLASS: A hybrid method to generate optimized fuzzy partitions for classification","volume":"16","author":"Cadenas","year":"2012","journal-title":"Soft Comput."},{"key":"ref_33","first-page":"87","article-title":"Study of high-dimensional fuzzy classification based on random forest algorithm","volume":"2","author":"Zhang","year":"2014","journal-title":"Remote Sens. Land Resour."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1080\/136588199241373","article-title":"Processing fuzzy spatial queries: A configuration similarity approach","volume":"13","author":"Papadias","year":"1999","journal-title":"Int. J. Geogr. Inf. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/2\/58\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:54:11Z","timestamp":1760194451000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/2\/58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,7]]},"references-count":35,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,2]]}},"alternative-id":["ijgi7020058"],"URL":"https:\/\/doi.org\/10.3390\/ijgi7020058","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2018,2,7]]}}}