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Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge

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Abstract

Spatio-temporal geological big data contain a large amount of spatial and nonspatial data. It is important to effectively manage and retrieve these existing data for geological research, and understanding the question represents the first step. This paper aims to better understand the problem to improve the retrieval efficiency. In geology, the organization of massive unstructured geological data and the discovery of implicit content based on knowledge and relationships have been realized. However, previous findings are primarily based on spatial and nonspatial dimensions, and the key words searched are often just segmented words. In geological research, the dimension of time is as important as spatial and other nonspatial dimensions. In addition, an individual user’s goal may be more than a superficial representation of the problem. In this paper, we first construct the geological event ontology, organize Spatio-temporal big data with this dimension, and expand the concept of geological time. Next, based on geology knowledge, we propose spatio-temporal rules, spatial characteristics, and domain constraint rules to assess the consistency of the ontology and to maximize the relationship between the information and improvements in the efficiency of information retrieval. Then, the ontology question is extended, and the rules between this question and other ontologies are expounded to deepen the understanding of the problem. Finally, we evaluate our contribution over a real geology dataset on a knowledge-driven geologic survey information smart-service platform (GSISSP), which integrates geological thematic ontology, geological temporal ontology, and toponymy ontology. This study reveals a positive impact of the incorporation of multiple ontologies and feature rules, which is meaningful for improving accuracy and comprehensiveness.

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References

  • Abadi A, Ben-Azza H, Sekkat S (2018) Improving integrated product design using SWRL rules expression and ontology-based reasoning. Procedia Computer Science 127:416–425

    Article  Google Scholar 

  • Adderly DM, Allen CO, Tucker RK (2018) Intelligence gathering and analysis using a question answering system. US: International Business Machines Corporation (Armonk, NY, US)

  • Aminu EF, Oyelade ON, Shehu IS (2016) Rule based communication protocol between social networks using semantic web rule language (SWRL). International Journal of Modern Education and Computer Science 8:22–29

    Article  Google Scholar 

  • Ben Abacha A, Zweigenbaum P (2015) MEANS: a medical question-answering system combining NLP techniques and semantic web technologies. Inf Process Manag 51:570–594

    Article  Google Scholar 

  • Bogdanović M, Stanimirović A, Stoimenov L (2015) Methodology for geospatial data source discovery in ontology-driven geo-information integration architectures. Web Semantics Science Services & Agents on the World Wide Web 32:1–15

    Article  Google Scholar 

  • Chandiok A, Chaturvedi DK (2018) Cognitive functionality based question answering system. Int J Comput Appl 179:1–6

    Google Scholar 

  • Cox SJD (2015) Time ontology extended for non-Gregorian calendar applications. 7:201–209

    Article  Google Scholar 

  • Deng J, Wang Z, Yuan J (2011) Qualitative reasoning with spatial direction relations based on geo-ontology. Computer Programming Skills & Maintenance 20:133–136

  • Doubravova J, Wiszniowski J, Horalek J (2016) Single layer recurrent neural network for detection of swarm-like earthquakes in W-Bohemia/Vogtland-the method. Comput Geosci 93:138–149

    Article  Google Scholar 

  • Frasincar F, Milea V, Kaymak U (2010) tOWL: integrating time in OWL. Springer, Berlin Heidelberg

    Google Scholar 

  • Han SY, Tsou M-H, Clarke KC (2017) Revisiting the death of geography in the era of Big Data the friction of distance in cyberspace and real space. International Journal of Digital Earth 1–19

  • Henriksson A, Kvist M, Dalianis H, Duneld M (2015) Identifying adverse drug event information in clinical notes with distributional semantic representations of context. J Biomed Inform 57:333–349

    Article  Google Scholar 

  • Hohenecker P, Lukasiewicz T (2017) Deep learning for ontology reasoning

  • Hong M-D, Oh K-J, Go S-H, Jo G-S (2016) Temporal ontology representation and reasoning using ordinals and sets for historical events. In: Nguyen NT, Trawiński B, Fujita H, Hong T-P (eds) Intelligent information and database systems. Springer-Verlag, pp 75–85

  • Horrocks I, Patel-Schneider PF, Boley H, Tabet S, Grosof B, Dean M (2004) SWRL introduction. http://www.daml.org/2003/11/swrl/

  • Hou Z, Zhu Y, Gao X, Luo K, Wang D, Kai S (2015) A Chinese geological time scale ontology for geodata discovery. In: Geoinformatics, 2015 23rd international conference on. IEEE, Wuhan, pp 1–5

    Google Scholar 

  • Hudelot C, Atif J, Bloch I (2008) A spatial relation ontology using mathematical morphology and description logics for spatial reasoning

  • Idoudi R, Ettabaa KS, Hamrouni K, Solaiman B (2014) An evidence based approach for multipe similarity measures combining for ontology mapping. Image Processing, Applications & Systems Conference

  • Jetinai K, Arch-int N, Arch-int S (2016) Ontology mapping and rule-based inference for learning resource integration. Journal of Information and Communication Convergence Engineering 14:97–105

    Article  Google Scholar 

  • Jia Shu S, Ru Gao C (1989) Preliminary exploration of the element's memory of geological events. J Geom:149–166

  • Jianping C, Jing L, Ning C, Pingping Y (2015) The construction and application of geological cloud under the big data background. Geological Bulletin of China 34:1260–1265

    Google Scholar 

  • Kaminski M, Nenov Y, Grau BC (2014) Datalog Rewritability of Disjunctive Datalog Programs and its Applications to Ontology Reasoning

  • Klyuev V, Oleshchuk V (2011) Semantic retrieval: an approach to representing, searching and summarising text documents. Int J Inf Technol Commun Converg 1:221–234

    Google Scholar 

  • Lakshmi Tulasi R, Rao MS, Ankita K, Hgoudar R (2017) Ontology-based automatic annotation: an approach for efficient retrieval of semantic results of web documents. In: Satapathy SC, Prasad VK, Rani BP, Udgata SK, Raju KS (eds) Proceedings of the First International Conference on Computational Intelligence and Informatics. Springer, Singapore, Singapore, pp 331–339

    Chapter  Google Scholar 

  • Lezcano L, Sicilia MA, Rodríguezsolano C (2011) Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules. J Biomed Inform 44:343–353

    Article  Google Scholar 

  • Liu XH, Cui J, Cai F (2018) Geo-ontology modeling and reasoning of Geohazard emergency response knowledge. Geography and Geo-Information Science

  • Lu S, Li K, Yu H (2001) Geological events, event sequence and event group. Geological Review 49:521–526

    Google Scholar 

  • Ma X, Carranza EJM, Wu C, van der Meer FD (2012) Ontology-aided annotation, visualization, and generalization of geological time-scale information from online geological map services. Comput Geosci 40:107–119

    Article  Google Scholar 

  • Ma X, Erickson JS, Zednik S, West P, Fox P (2016) Semantic specification of data types for a world of open data. ISPRS Int J Geo Inf 5:38

    Article  Google Scholar 

  • Mayer-Schnberger, Cukier VK (2013) Big data: a revolution that will transform how we live, work, and think. Eamon Dolan/Houghton Mifflin Harcourt

  • Mervin R, Jaya A (2018) A novel approach to mapping for KBQA system using ontology. In: Shetty NR, Patnaik LM, Prasad NH, Nalini N (eds) ERCICA 2016: Emerging Research in Computing, Information, Communication and Applications. Springer, Singapore, Singapore, pp 89–97

    Chapter  Google Scholar 

  • Narayanan S, Harabagiu S (2004) Question answering based on semantic structures

  • Pavlić M, Han ZD, Jakupović A (2015) Question answering with a conceptual framework for knowledge-based system development "node of knowledge". Expert Syst Appl 42:5264–5286

    Article  Google Scholar 

  • Perera ARP (2018) A framework for generating informative answers for question answering systems. Auckland University of Technology

  • Recommendation WC (2017) Time ontology in OWL. https://www.w3.org/TR/owl-time/

  • Schadd FC, Roos N (2014) Word-sense disambiguation for ontology mapping: concept disambiguation using virtual documents and Information retrieval techniques. Journal on Data Semantics 4:167–186

    Article  Google Scholar 

  • Shen D, Lapata M (2007) Using semantic roles to improve question answering// EMNLP-CoNLL 2007, Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, June 28-30, 2007, Prague, Czech Republic

  • Song Nian L, Guo Jie H, Zhen Qun X (2016) Major Precambrian geological events. Earth Science Frontiers 23:140–155

    Google Scholar 

  • Varzi AC (2007) Spatial reasoning and ontology: parts, wholes, and locations. Springer Netherlands

    Google Scholar 

  • Wagemann J, Clements O, Figuera RM, Rossi AP, Mantovani S (2017) Geospatial web services pave new ways for server based on demand access and processing of Big Earth Data. International Journal of Digital Earth 11:7–25

    Article  Google Scholar 

  • Wang W, Stewart K (2015) Spatiotemporal and semantic information extraction from web news reports about natural hazards. Comput Environ Urban Syst 50:30–40

    Article  Google Scholar 

  • Wang C, Ma X, Chen J (2018) Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information. Comput Geosci 115:12–19

    Article  Google Scholar 

  • Wu L, Xue L, Li C, Lv X, Chen Z, Jiang B, Guo M, Xie Z (2017) A knowledge-driven geospatially enabled framework for geological big data. ISPRS Int J Geo Inf 6:166

    Article  Google Scholar 

  • Xing FK (2015) Domain entities discovery based on Wikipedia. Application Research of Computers

  • Xu J, Nyerges TL, Nie G (2014) Modeling and representation for earthquake emergency response knowledge: perspective for working with geo-ontology. Int J Geogr Inf Sci 28:185–205

    Article  Google Scholar 

  • Yang YH, Du JP, Ping Y (2015) Ontology-based intelligent information retrieval system. Ruan Jian Xue Bao/Journal of Software 26(7):1675−1687 (in Chinese). http://www.jos.org.cn/1000-9825/4622.htm

  • Yang C, Yu M, Hu F, Jiang Y, Li Y (2017) Utilizing cloud computing to address big geospatial data challenges. Comput Environ Urban Syst 61:120–128

    Article  Google Scholar 

  • Zhang LY, Tao BR (2015) Ontology mapping based on Bayesian network. Journal of Donghua University 32:681–687

    Google Scholar 

  • Zheng L, Li X (2008) An ontology reasoning architecture for data mining knowledge management. Wuhan University Journal of Natural Sciences 13:396–400

    Article  Google Scholar 

  • Zhou G, Zhao J, He T, Wu W (2014) An empirical study of topic-sensitive probabilistic model for expert finding in question answer communities. Knowl-Based Syst 66:136–145

    Article  Google Scholar 

Download references

Acknowledgments

This project was supported by the National Science Foundation of China (Grant No. 41871311, 41671400) and the National Key Research and Development Program (Grant No. 2017YFB0503600, 2017YFC0602204, 2018YFB0505500). The authors thank the Development and Research Center of the China Geological Survey for providing technical support. We thank the National Engineering Research Center of Geographic Information System for providing hardware support.

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Authors and Affiliations

  1. Faculty of Information Engineering, China University of Geosciences, Wuhan, 430074, China

    Wenjia Li, Liang Wu, Zhong Xie & Kuanmao Zou

  2. National Engineering Research Center for GIS, Wuhan, 430074, China

    Liang Wu, Zhong Xie & Liufeng Tao

  3. Development and Research Center, China Geological Survey, Beijing, 100037, China

    Fengdan Li & Jinli Miao

Authors
  1. Wenjia Li
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  2. Liang Wu
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  3. Zhong Xie
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  4. Liufeng Tao
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  5. Kuanmao Zou
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  6. Fengdan Li
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  7. Jinli Miao
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Contributions

Conceived and designed the experiments: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Performed the experiments: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Analyzed the data: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Wrote the paper: Wenjia Li, Liang Wu and Zhong Xie.

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Correspondence to Liang Wu.

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Communicated by: H. Babaie

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Li, W., Wu, L., Xie, Z. et al. Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge. Earth Sci Inform 12, 599–613 (2019). https://doi.org/10.1007/s12145-019-00402-2

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