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Research Articles

A grammar for interpreting geo-analytical questions as concept transformations

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Pages 276-306 | Received 14 Nov 2021, Accepted 11 May 2022, Published online: 30 May 2022

References

  • Aho, A.V., et al., 2007. Compilers: principles, techniques, & tools. Boston, MA: Pearson Addison Wesley.
  • Allen, D., 2013. GIS tutorial 2: spatial analysis workbook. Redlands: Esri Press.
  • Bao, J., et al., 2016. Constraint-based question answering with knowledge graph. In: Proceedings of COLING 2016, the 26th international conference on computational linguistics: technical papers, 2503–2514.
  • Buzaaba, H. and Amagasa, T., 2021. Question answering over knowledge base: a scheme for integrating subject and the identified relation to answer simple questions. SN Computer Science, 2 (1), 1–13.
  • Ceri, S., et al., 2013. An introduction to information retrieval. In: Web information retrieval. Springer, 3–11.
  • Chen, W., et al., 2013. A synergistic framework for geographic question answering. In: 2013 IEEE seventh international conference on semantic computing. New York, NY: IEEE Press, 94–99.
  • Chen, W., et al., 2020. Hybridqa: A dataset of multi-hop question answering over tabular and textual data. arXiv preprint arXiv:2004.07347.
  • Devlin, J., et al., 2018. Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
  • Diefenbach, D., et al., 2018. Core techniques of question answering systems over knowledge bases: a survey. Knowledge and Information Systems, 55 (3), 529–569.
  • Dozat, T. and Manning, C.D., 2016. Deep biaffine attention for neural dependency parsing. arXiv preprint arXiv:1611.01734.
  • Fader, A., Zettlemoyer, L., and Etzioni, O., 2014. Open question answering over curated and extracted knowledge bases. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, 1156–1165.
  • Hamzei, E., et al., 2019., Place questions and human-generated answers: a data analysis approach. In: Proceedings of the 22nd AGILE conference on geographic information science. Cham: Springer International Publishing, 3–19.
  • Hamzei, E., Winter, S., and Tomko, M., 2022. Templates of generic geographic information for answering where-questions. International Journal of Geographical Information Science, 36 (1), 188–127.
  • Heywood, I., Cornelius, S., and Carver, S., 2011. An introduction to geographical information systems. Harlow: Pearson Education Limited.
  • Hopcroft, J.E., Motwani, R., and Ullman, J.D., 2006. Automata theory, languages, and computation. International Edition, 24 (2), 171–183.
  • Huang, Z., et al., 2019. Geosqa: A benchmark for scenario-based question answering in the geography domain at high school level. arXiv preprint arXiv:1908.07855.
  • Kapanipathi, P., et al., 2021. Leveraging abstract meaning representation for knowledge base question answering. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 3884–3894.
  • Kraak, M. and Ormeling, F., 2013. Cartography: visualization of spatial data. Boca Raton, FL: CRC Press.
  • Kruiger, J.F., et al., 2021. Loose programming of GIS workflows with geo-analytical concepts. Transactions in GIS, 25 (1), 424–449.
  • Kuhn, W., 2012. Core concepts of spatial information for transdisciplinary research. International Journal of Geographical Information Science, 26 (12), 2267–2276.
  • Kuhn, W. and Ballatore, A., 2015. Designing a language for spatial computing. In: Agile 2015. Cham: Springer, 309–326.
  • Lukovnikov, D., et al., 2017. Neural network-based question answering over knowledge graphs on word and character level. In: Proceedings of the 26th international conference on world wide web, 1211–1220.
  • Mador-Haim, S., Winter, Y., and Braun, A., 2006. Controlled language for geographical information system queries. In: Proceedings of the fifth international workshop on inference in computational semantics (ICoS-5).
  • Mai, G., et al., 2021. Geographic question answering: challenges, uniqueness, classification, and future directions. AGILE: GIScience Series, 2, 1–21. Available from: https://agile-giss.copernicus.org/articles/2/8/2021/.
  • Mai, G., et al., 2019a. Deeply integrating linked data with geographic information systems. Transactions in GIS, 23 (3), 579–600.
  • Mai, G., et al., 2019b. Relaxing unanswerable geographic questions using a spatially explicit knowledge graph embedding model. In: The annual international conference on geographic information science. Cham: Springer International Publishing, 21–39.
  • Mohit, B., 2014. Named entity recognition. In: Natural language processing of semitic languages. Berlin, Heidelberg: Springer, 221–245.
  • Nyerges, T.L., 1995. Cognitive issues in the evolution of GIS user knowledge. In: Cognitive aspects of human-computer interaction for geographic information systems. Dordrecht: Springer, 61–74.
  • O’Looney, J., 2000. Beyond maps: GIS and decision making in local government. Redlands: ESRI Press.
  • Punjani, D., et al., 2018. Template-based question answering over linked geospatial data. In: Proceedings of the 12th workshop on geographic information retrieval, 1–10.
  • Sagara, T. and Hagiwara, M., 2014. Natural language neural network and its application to question-answering system. Neurocomputing, 142, 201–208.
  • Scheider, S. and Huisjes, M.D., 2019. Distinguishing extensive and intensive properties for meaningful geocomputation and mapping. International Journal of Geographical Information Science, 33 (1), 28–54.
  • Scheider, S. and Lemmens, R., 2017. Using SPARQL to describe GIS methods in terms of the questions they answer. In: Societal geo-innovation: short papers, posters and poster abstracts of the 20th AGILE conference on geographic information science. LEI Wageningen University and Research Centre.
  • Scheider, S., et al., 2020a. Ontology of core concept data types for answering geo-analytical questions. Journal of Spatial Information Science, 2020 (20), 167–201.
  • Scheider, S., et al., 2020b. Geo-analytical question-answering with GIS. International Journal of Digital Earth, 14 (1), 1–14.
  • Schwitter, R., 2005. A controlled natural language layer for the semantic web. In: Australasian joint conference on artificial intelligence. Springer, 425–434.
  • Sinton, D., 1978. The inherent structure of information as a constraint to analysis: mapped thematic data as a case study. Harvard papers on geographic information systems.
  • Ten Berge, T. and Van Hezewijk, R., 1999. Procedural and declarative knowledge: an evolutionary perspective. Theory & Psychology, 9 (5), 605–624.
  • Wielemann, J., 2019. The semantic structure of spatial questions in human geography. Thesis (Masters). Utrecht University. Available from: https://dspace.library.uu.nl/bitstream/handle/1874/384695/Thesis_Report_Joris_Wieleman.pdf.
  • Xu, H., et al., 2020. Extracting interrogative intents and concepts from geo-analytic questions. AGILE: GIScience Series, 1, 1–21.
  • Yang, W., et al., 2019. End-to-end open-domain question answering with bertserini. arXiv preprint arXiv:1902.01718.
  • Yin, X., Gromann, D., and Rudolph, S., 2021. Neural machine translating from natural language to SPARQL. Future Generation Computer Systems, 117, 510–519.
  • Zuva, K. and Zuva, T., 2012. Evaluation of information retrieval systems. International Journal of Computer Science and Information Technology, 4 (3), 35–43.