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Wei Chen Dissertation Final.pdf (3.13 MB)

ETD Abstract Container

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Developing a Framework for Geographic Question Answering Systems Using GIS, Natural Language Processing, Machine Learning, and Ontologies

Chen, Wei
http://rave.ohiolink.edu/etdc/view?acc_num=osu1388065704

Abstract Details

2014, Doctor of Philosophy, Ohio State University, Geography.
Geographic question answering (QA) systems can be used to help make geographic knowledge accessible by directly giving answers to natural language questions. In this dissertation, a geographic question answering (GeoQA) framework is proposed by incorporating techniques from natural language processing, machine learning, ontological reasoning and geographic information system (GIS). We demonstrate that GIS functions provide valuable rule-based knowledge, which may not be available elsewhere, for answering geographic questions. Ontologies of space are developed to interpret the meaning of linguistic spatial terms which are later mapped to components of a query in a GIS; these ontologies are shown to be indispensable during each step of question analysis. A customized classifier based on dynamic programming and a voting algorithm is also developed to classify questions into answerable categories. To prepare a set of geographic questions, we conducted a human survey and generalized four categories that have the most questions for experiments. These categories were later used to train a classifier to classify new questions. Classified natural language questions are converted to spatial SQLs to retrieve data from relational databases. Consequently, our demo system is able to give exact answers to four categories of geographic questions within an average time of two seconds. The system has been evaluated using classical machine learning-based measures and achieved an overall accuracy of 90% on test data. Results show that spatial ontologies and GIS are critical for extending the capabilities of a GeoQA system. Spatial reasoning of GIS makes it a powerful analytical engine to answer geographic questions through spatial data modeling and analysis.
Eric Fosler-Lussier, Dr. (Committee Member)
Rajiv Ramnath, Dr. (Committee Member)
Daniel Sui, Dr. (Committee Member)
Ningchuan Xiao, Dr. (Committee Chair)
177 p.
Cognitive Psychology; Computer Science; Geographic Information Science; Geography; Information Science; Information Systems; Information Technology; Language
geographic information system; GeoQA; geographic question answering framework; geolinguistics; spatial ontologies;

Recommended Citations

Citations

  • Chen, W. (2014). Developing a Framework for Geographic Question Answering Systems Using GIS, Natural Language Processing, Machine Learning, and Ontologies [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388065704

    APA Style (7th edition)

  • Chen, Wei. Developing a Framework for Geographic Question Answering Systems Using GIS, Natural Language Processing, Machine Learning, and Ontologies. 2014. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1388065704.

    MLA Style (8th edition)

  • Chen, Wei. "Developing a Framework for Geographic Question Answering Systems Using GIS, Natural Language Processing, Machine Learning, and Ontologies." Doctoral dissertation, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388065704

    Chicago Manual of Style (17th edition)

osu1388065704
787
© 2014, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.