Infrastructure Engineering - Research Publications

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Author: Hamzei, Ehsan × Author: Li, Haonan × Author: Tomko, Martin × Author: Winter, Stephan × End date: 2022 × Start date: 2020 × Type: Journal Article ×

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    Neural factoid geospatial question answering
    Li, H ; Hamzei, E ; Majic, I ; Hua, H ; Renz, J ; Tomko, M ; Vasardani, M ; Winter, S ; Baldwin, T (UNIV MAINE, 2021)
    Existing question answering systems struggle to answer factoid questions when geospatial information is involved. This is because most systems cannot accurately detect the geospatial semantic elements from the natural language questions, or capture the semantic relationships between those elements. In this paper, we propose a geospatial semantic encoding schema and a semantic graph representation which captures the semantic relations and dependencies in geospatial questions. We demonstrate that our proposed graph representation approach aids in the translation from natural language to a formal, executable expression in a query language. To decrease the need for people to provide explanatory information as part of their question and make the translation fully automatic, we treat the semantic encoding of the question as a sequential tagging task, and the graph generation of the query as a semantic dependency parsing task. We apply neural network approaches to automatically encode the geospatial questions into spatial semantic graph representations. Compared with current template-based approaches, our method generalises to a broader range of questions, including those with complex syntax and semantics. Our proposed approach achieves better results on GeoData201 than existing methods.
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    The semantics of place-related questions
    Kuhn, W ; Hamzei, E ; Tomko, M ; Winter, S ; Li, H (UNIV MAINE, 2021)
    The trend to equip information systems with question-answering capabilities raises the design problem of deciding which questions a system should be able to answer. Typical solutions build on mining human conversations or logs from similar systems for question patterns. For the case of questions about geographic places, we present a complementary approach, showing how to derive possible questions from an ontology of spatial information and a classification of place facets. We argue that such an approach reduces the inherent and substantial data bias of current solutions. At a more general level, we provide a novel understanding of spatial questions and their role in designing and using spatial information systems.