Similarity matching for integrating spatial information extracted from place descriptions

References

• Abdelkader, A., Hand, E., and Samet, H., 2015. Brands in NewsStand: spatio-temporal browsing of business news. In: J. Bao, et al., eds. Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 3–6 November, Bellevue, WA. New York: ACM, 1–4.
   Google Scholar
• Adams, B., McKenzie, G., and Gahegan, M., 2015. Frankenplace: interactive thematic mapping for ad hoc exploratory search. In: A. Gangemi, S. Leonardi, and A. Panconesi, eds. Proceedings of the 24th International Conference on World Wide Web, 18–22 May, Florence. New York: ACM, 12–22.
   Google Scholar
• Amitay, E., et al., 2004. Web-a-where: geotagging web content. In: M. Sanderson, et al., eds. Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 25–29 July, Sheffield. New York: ACM, 273–280.
   Google Scholar
• Ballatore, A., Bertolotto, M., and Wilson, D.C., 2013. Grounding linked open data in WordNet: the case of the OSM semantic network. In: S.H.L. Liang, X. Wang, and C. Claramunt, eds. Proceedings of the Web and Wireless Geographical Information Systems International Symposium, 4–5 April, Banff, AB. Berlin: Springer, 1–15.
   Google Scholar
• Ballatore, A., Bertolotto, M., and Wilson, D.C., 2014. The semantic similarity ensemble. Journal of Spatial Information Science (JOSIS), 7, 27–44.
   Google Scholar
• Banerjee, S. and Pedersen, T., 2002. An adapted Lesk algorithm for word sense disambiguation using WordNet. In: A.F. Gelbukh, ed. Computational Linguistics and Intelligent Text Processing, 17–23 February, Mexico City. Berlin: Springer, 136–145.
   Google Scholar
• Bennett, B. and Agarwal, P., 2007. Semantic categories underlying the meaning of ‘place’. In: S. Winter, et al., eds. Spatial Information Theory, 19–23 September, Melbourne. Berlin: Springer, 78–95.
   Google Scholar
• Duckham, M., Winter, S., and Robinson, M., 2010. Including landmarks in routing instructions. Journal of Location Based Services, 4 (1), 28–52. doi:10.1080/17489721003785602
   Google Scholar
• Egenhofer, M.J., 1994. Deriving the composition of binary topological relations. Journal of Visual Languages & Computing, 5 (2), 133–149. doi:10.1006/jvlc.1994.1007
   Web of Science ®Google Scholar
• Egenhofer, M.J. and Herring, J.R., 1991. Categorizing binary topological relationships between regions, lines, and points in geographic databases. Technical Report. Orono, ME: Department of Surveying Engineering, University of Maine.
   Google Scholar
• Egenhofer, M.J. and Sharma, J., 1993. Assessing the consistency of complete and incomplete topological information. Geographical Systems, 1 (1), 47–68.
   Google Scholar
• Euzenat, J., et al., 2013. Ontology Matching. Vol. 2. Berlin: Springer.
   Google Scholar
• Fellbaum, C., 1998. WordNet: An Electronic Lexical Database. Cambridge, MA: MIT Press.
   Google Scholar
• Fellbaum, C., 2010. Wordnet. In: R. Poli, M. Healy, and A. Kameas, eds. Theory and Applications of Ontology: Computer Applications. Dordrecht: Springer, 231–243.
   Google Scholar
• Frank, A.U., 1992. Qualitative spatial reasoning about distances and directions in geographic space. Journal of Visual Languages & Computing, 3 (4), 343–371. doi:10.1016/1045-926X(92)90007-9
   Google Scholar
• Franz, G., Mallot, H.A., and Wiener, J.M., 2005. Graph-based models of space in architecture and cognitive science - a comparative analysis. In: G.E. Lasker, ed. Proceedings of the 17th International Conference on Systems Research, Informatics and Cybernetics, 1–7 August, Baden. Windsor, ON: International Institute for Advanced Studies in Systems Research and Cybernetics, 30–38.
   Google Scholar
• Freksa, C., 1992. Using orientation information for qualitative spatial reasoning. In: A.U. Frank, I. Campari, and U. Formentini, eds. Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, Vol. 639 of Lecture Notes in Computer Science. Berlin: Springer, 162–178.
   Google Scholar
• Hernandez, D., 1991. Relative representation of spatial knowledge: the 2-D case. In: D.M. Mark and A.U. Frank, eds. Cognitive and Linguistic Aspects of Geographic Space. Dordrecht: Springer, 373–385.
   Google Scholar
• Hidders, J., 2002. Typing graph-manipulation operations. In: D. Calvanese, M. Lenzerini, and R. Motwani, eds. Database Theory – ICDT 2003, Vol. 2572 of Lecture Notes in Computer Science. Berlin: Springer, 394–409.
   Google Scholar
• Janowicz, K., Raubal, M., and Kuhn, W., 2011. The semantics of similarity in geographic information retrieval. Journal of Spatial Information Science, 2011 (2), 29–57.
   Google Scholar
• Jones, C.B. and Purves, R.S., 2008. Geographical information retrieval. International Journal of Geographical Information Science, 22 (3), 219–228. doi:10.1080/13658810701626343
   Web of Science ®Google Scholar
• Keßler, C., Janowicz, K., and Bishr, M., 2009. An agenda for the next generation gazetteer: geographic information contribution and retrieval. In: D. Agrawal, et al., eds. Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 4–6 November, Seattle, WA. New York, NY: ACM, 91–100.
   Google Scholar
• Khan, A., Vasardani, M., and Winter, S., 2013. Extracting spatial information from place descriptions. In: S. Scheider, et al., eds. Proceedings of the First ACM SIGSPATIAL International Workshop on Computational Models of Place, 5 November, Orlando, FL. New York, NY: ACM, 62–69.
   Google Scholar
• Kim, J., Vasardani, M., and Winter, S., 2015a. From descriptions to depictions: a dynamic sketch map drawing strategy. Spatial Cognition & Computation, 16 (1), 29–53. doi:10.1080/13875868.2015.1084509
   Web of Science ®Google Scholar
• Kim, J., Vasardani, M., and Winter, S., 2015b. Harvesting large corpora for generating place graphs. In: S. Bertel, et al., eds. International Workshop on Cognitive Engineering for Spatial Information Processes: From User Interfaces to Model-Driven Design, in Conjunction with COSIT 2015, 12 October, Santa Fe, NM. CESIP.
   Google Scholar
• Kleinberg, J.M., 2000. Authoritative sources in a hyperlinked environment. Journal of the ACM, 46 (5), 604–632. doi:10.1145/324133.324140
   Web of Science ®Google Scholar
• Kuhn, H.W., 1955. The Hungarian method for the assignment problem. Naval Research Logistics Quarterly, 2 (1–2), 83–97. doi:10.1002/(ISSN)1931-9193
   Google Scholar
• Landau, B. and Jackendoff, R., 1993. “What” and “Where” in spatial language and spatial cognition. Behavioral and Brain Sciences, 16 (2), 217–238. doi:10.1017/S0140525X00029733
   Web of Science ®Google Scholar
• Leacock, C. and Chodorow, M., 1998. Combining local context and WordNet similarity for word sense identification. Wordnet: an Electronic Lexical Database, 49 (2), 265–283.
   Google Scholar
• Levenshtein, V.I., 1966. Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady, 10 (8), 707–710.
   Google Scholar
• Liu, F., Vasardani, M., and Baldwin, T., 2014. Automatic identification of locative expressions from social media text: a comparative analysis. In: D. Ahlers, E. Wilde, and B. Martins, eds. Proceedings of the 4th International Workshop on Location and the Web, 3 November, Shanghai. New York: ACM, 9–16.
   Google Scholar
• Manning, C.D. and Schütze, H., 1999. Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press.
   Google Scholar
• Martins, B., 2011. A supervised machine learning approach for duplicate detection over gazetteer records. In: C. Claramunt, S. Levashkin, and M. Bertolotto, eds. Proceedings of the 4th International Conference on Geospatial Semantics, 12–13 May, Brest. Berlin: Springer, 34–51.
   Google Scholar
• Mata, F., 2007. Geographic information retrieval by topological, geographical, and conceptual matching. In: F.T. Fonseca, M.A. Rodrıguez, and S. Levashkin, eds. GeoSpatial Semantics. Berlin: Springer, 98–113.
   Google Scholar
• McKenzie, G., Janowicz, K., and Adams, B., 2014. A weighted multi-attribute method for matching user-generated points of interest. Cartography and Geographic Information Science, 41 (2), 125–137. doi:10.1080/15230406.2014.880327
   Web of Science ®Google Scholar
• Melnik, S., Garcia-Molina, H., and Rahm, E., 2002. Similarity flooding: a versatile graph matching algorithm and its application to schema matching. In: R. Agrawal and K.R. Dittrich, eds. Proceedings of the 18th International Conference on Data Engineering, 26 March–1 February, San Jose, CA. IEEE Computer Society, 117–128.
   Google Scholar
• Mihalcea, R., Corley, C., and Strapparava, C., 2006. Corpus-based and knowledge-based measures of text semantic similarity. Association for the Advancement of Artificial Intelligence (AAAI), 6, 775–780.
   Google Scholar
• Miller, G.A., 1995. WordNet: a lexical database for English. Communications of the ACM, 38 (11), 39–41. doi:10.1145/219717.219748
   Web of Science ®Google Scholar
• Nadeau, D., Turney, P., and Matwin, S., 2006. Unsupervised named-entity recognition: generating gazetteers and resolving ambiguity. In: L. Lamontagne and M. Marchand, eds. Advances in Artificial Intelligence, 7–9 June, Quebec City, QC. Berlin: Springer, 266–277.
   Google Scholar
• Nedas, K.A. and Egenhofer, M.J., 2008. Spatial-Scene Similarity Queries. Transactions in GIS, 12 (6), 661–681. doi:10.1111/tgis.2008.12.issue-6
   Google Scholar
• Nurdiati, S. and Hoede, C., 2008. 25 years development of knowledge graph theory: the results and the challenges. Report. Enschede: Department of Applied Mathematics, University of Twente.
   Google Scholar
• Papadias, D., 1999. Processing fuzzy spatial queries: a configuration similarity approach. International Journal of Geographical Information Science, 13 (2), 93–118. doi:10.1080/136588199241373
   Web of Science ®Google Scholar
• Papadias, D. and Egenhofer, M.J., 1997. Algorithms for hierarchical spatial reasoning. Geoinformatica, 1 (3), 251–273. doi:10.1023/A:1009760430440
   Google Scholar
• Papadias, D. and Kavouras, M., 1994. Acquiring, representing and processing spatial relations. In: T.C. Waugh, ed. Proceedings of the 6th International Symposium on Spatial Data Handling. Edinburgh: Taylor & Francis.
   Google Scholar
• Patwardhan, S. and Pedersen, T., 2006. Using WordNet-based context vectors to estimate the semantic relatedness of concepts. In: N. Ide and C. Fellbaum, eds. Proceedings of Making Sense of Sense: Bringing Computational Linguistics and Psycholinguistics Together, 4 April, Trento. East Stroudsburg, PA: EACL, 1–8.
   Google Scholar
• Pedersen, T., Patwardhan, S., and Michelizzi, J., 2004. WordNet: similarity: measuring the relatedness of concepts. In: A.G. Cohn, ed. Proceedings of the 19th National Conference on Artificial Intelligence, 25–29 July, San Jose, CA. Palo Alto, CA: AAAI Press, 1024–1025.
   Google Scholar
• Pfeifer, U., Poersch, T., and Fuhr, N., 1995. Searching proper names in databases. In: R. Kuhlen and M. Rittberger, eds. Hypertext - Information Retrieval - Multimedia, 5–7 April, Konstanz. Konstanz: Universitatsverlag Konstanz, 259–275.
   Google Scholar
• Resnik, P., 1995. Using information content to evaluate semantic similarity in a taxonomy. In: C.S. Mellish, ed. Proceedings of the 14th International Joint Conference on Artificial Intelligence, Vol. 2, 20–25 August, Montrea, QC. San Mateo, CA: Morgan Kaufmann, 448–453.
   Google Scholar
• Resnik, P., 2011. Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research, 11, 95–130.
   Google Scholar
• Richter, D., et al., 2013. Zooming in–zooming out hierarchies in place descriptions. Lecture notes in geoinformation and cartography. In: J.M. Krisp, ed. Progress in Location-Based Services. Berlin: Springer, 339–355.
   Google Scholar
• Richter, K.F. and Winter, S., 2014. Landmarks: GIScience for Intelligent Services. Cham, Switzerland: Springer.
   Google Scholar
• Rodriguez, M.A. and Egenhofer, M.J., 2004. Comparing geospatial entity classes: an asymmetric and context-dependent similarity measure. International Journal of Geographical Information Science, 18 (3), 229–256. doi:10.1080/13658810310001629592
   Web of Science ®Google Scholar
• Scheffler, T., Schirru, R., and Lehmann, P., 2012. Matching points of interest from different social networking sites. In: B. Glimm and A. Kruger, eds. KI 2012: Advances in Artificial Intelligence, 24–27 September. Saarbrucken. Berlin: Springer, 245–248.
   Google Scholar
• Schwering, A., 2007a. Evaluation of a semantic similarity measure for natural language spatial relations. In: S. Winter, et al., eds. Spatial Information Theory, 19–23 September, Melbourne. Berlin: Springer, 116–132.
   Google Scholar
• Schwering, A., 2007b. Semantic Similarity Measurement Including Spatial Relations for Semantic Information Retrieval of Geo-Spatial Data. Thesis (PhD). Institut fur Geoinformatik, Universitat Munster.
   Google Scholar
• Sehgal, V., Getoor, L., and Viechnicki, P.D., 2006. Entity resolution in geospatial data integration. In: R.A. de By and S. Nittel, eds. Proceedings of the 14th Annual ACM International Symposium on Advances in Geographic Information Systems, 10–11 November, Arlington, VA. New York: ACM, 83–90.
   Google Scholar
• Shariff, A.R.B.M., Egenhofer, M.J., and Mark, D.M., 1998. Natural-language spatial relations between linear and areal objects: the topology and metric of English-language terms. International Journal of Geographical Information Science, 12 (3), 215–245.
   Web of Science ®Google Scholar
• Sowa, J.F., 1984. Conceptual Structures: Information Processing in Mind and Machine. Reading, MA: Addison-Wesley.
   Google Scholar
• Twaroch, F.A., Jones, C.B., and Abdelmoty, A.I., 2008. Acquisition of a Vernacular Gazetteer from web sources. In: S. Boll, et al., eds. Proceedings of the First International Workshop on Location and the Web, Vol. 300, 22 April, Beijing. New York, NY: ACM, 61–64.
   Google Scholar
• Vasardani, M., et al., 2013b. From descriptions to depictions: a conceptual framework. In: T. Tenbrink, et al., eds. Spatial Information Theory, 2–6 September, Scarborough. Berlin: Springer, 299–319.
   Google Scholar
• Vasardani, M., Winter, S., and Richter, K., 2013a. Locating place names from place descriptions. International Journal of Geographical Information Science, 27 (12), 2509–2532. doi:10.1080/13658816.2013.785550
   Web of Science ®Google Scholar
• West, D.B., 2001. Introduction to Graph Theory. Vol. 2. Upper Saddle River, NJ: Prentice hall.
   Google Scholar
• Winter, S., 2000. Location similarity of regions. ISPRS Journal of Photogrammetry and Remote Sensing, 55 (3), 189–200. doi:10.1016/S0924-2716(00)00019-8
   Web of Science ®Google Scholar
• Winter, S., 2003. Route adaptive selection of salient features. In: W. Kuhn, M. Worboys, and S. Timpf, eds. Spatial Information Theory, 24–28 September, Ittingen. Berlin: Springer, 349–361.
   Google Scholar
• Winter, S. and Freksa, C., 2012. Approaching the notion of place by contrast. Journal of Spatial Information Science, 2012 (5), 31–50.
   Google Scholar
• Wu, S. and Manber, U., 1992. Agrep–a fast approximate pattern-matching tool. In: E. Allman, ed. Proceedings of USENIX Winter 1992 Technical Conference, 20–24 January, San Francisco, CA. Berkeley, CA: USENIX, 153–162.
   Google Scholar
• Yi, S., Huang, B., and Chan, W.T., 2005. XML application schema matching using similarity measure and relaxation labeling. Information Sciences, 169 (1), 27–46. doi:10.1016/j.ins.2004.02.013
   Web of Science ®Google Scholar
• Zarembo, I., et al., 2015. Assessment of name based algorithms for land administration ontology matching. Procedia Computer Science, 43, 53–61. doi:10.1016/j.procs.2014.12.008
   Google Scholar
• Zheng, Y., et al., 2010. Detecting nearly duplicated records in location datasets. In: D. Agrawal, et al., eds. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, 3–5 November, San Jose, CA. New York: ACM, 137–143.
   Google Scholar