Infrastructure Engineering - Research Publications

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Author: Tomko, Martin × Start date: 2021 × Type: Conference Paper ×

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    Producer Conflict Management Approaches in Online Peer Production Communities - Case Study of OpenStreetMap
    Choe, Y ; Tomko, M ; Kalantari, M (ASSOC COMPUTING MACHINERY, 2023)
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    Assessing Mapper Conflict in OpenStreetMap Using the Delphi Survey Method
    Choe, Y ; Tomko, M ; Kalantari, M (ASSOC COMPUTING MACHINERY, 2023)
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    Spatial and Spatiotemporal Matching Framework for Causal Inference
    Akbari, K ; Tomko, M (Schloss Dagstuhl, 2022-09-01)
    Matching is a procedure aimed at reducing the impact of observational data bias in causal analysis. Designing matching methods for spatial data reflecting static spatial or dynamic spatio-temporal processes is complex because of the effects of spatial dependence and spatial heterogeneity. Both may be compounded with temporal lag in the dependency effects on the study units. Current matching techniques based on similarity indexes and pairing strategies need to be extended with optimal spatial matching procedures. Here, we propose a decision framework to support analysts through the choice of existing matching methods and anticipate the development of specialized matching methods for spatial data. This framework thus enables to identify knowledge gaps.
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    MultiSpanQA: A Dataset for Multi-Span Question Answering
    Li, H ; Vasardani, M ; Tomko, M ; Baldwin, T (ASSOC COMPUTATIONAL LINGUISTICS-ACL, 2022)
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    Translating Place-Related Questions to GeoSPARQL Queries
    Hamzei, E ; Tomko, M ; Winter, S (ASSOC COMPUTING MACHINERY, 2022)
    Many place-related questions can only be answered by complex spatial reasoning, a task poorly supported by factoid question retrieval. Such reasoning using combinations of spatial and non-spatial criteria pertinent to place-related questions is increasingly possible on linked data knowledge bases. Yet, to enable question answering based on linked knowledge bases, natural language questions must first be re-formulated as formal queries. Here, we first present an enhanced version of YAGO2geo, the geospatially-enabled variant of the YAGO2 knowledge base, by linking and adding more than one million places from OpenStreetMap data to YAGO2. We then propose a novel approach to translate the place-related questions into logical representations, theoretically grounded in the core concepts of spatial information. Next, we use a dynamic template-based approach to generate fully executable GeoSPARQL queries from the logical representations. We test our approach using the Geospatial Gold Standard dataset and report substantial improvements over existing methods.