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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Online-Zugang: | https://arxiv.org/abs/2412.02400 |
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| _version_ | 1866913595744321536 |
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| author | Razouk, Houssam Leitner, Michael Kern, Roman |
| author_facet | Razouk, Houssam Leitner, Michael Kern, Roman |
| contents | Urban blight is a problem of high interest for planning and policy making. Researchers frequently propose theories about the relationships between urban blight indicators, focusing on relationships reflecting causality. In this paper, we improve on the integration of domain knowledge in the analysis of urban blight by introducing four rules for effective modeling of causal domain knowledge. The findings of this study reveal significant deviation from causal modeling guidelines by investigating cognitive maps developed for urban blight analysis. These findings provide valuable insights that will inform future work on urban blight, ultimately enhancing our understanding of urban blight complex interactions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_02400 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Four Guiding Principles for Modeling Causal Domain Knowledge: A Case Study on Brainstorming Approaches for Urban Blight Analysis Razouk, Houssam Leitner, Michael Kern, Roman Computational Engineering, Finance, and Science Computation and Language Urban blight is a problem of high interest for planning and policy making. Researchers frequently propose theories about the relationships between urban blight indicators, focusing on relationships reflecting causality. In this paper, we improve on the integration of domain knowledge in the analysis of urban blight by introducing four rules for effective modeling of causal domain knowledge. The findings of this study reveal significant deviation from causal modeling guidelines by investigating cognitive maps developed for urban blight analysis. These findings provide valuable insights that will inform future work on urban blight, ultimately enhancing our understanding of urban blight complex interactions. |
| title | Four Guiding Principles for Modeling Causal Domain Knowledge: A Case Study on Brainstorming Approaches for Urban Blight Analysis |
| topic | Computational Engineering, Finance, and Science Computation and Language |
| url | https://arxiv.org/abs/2412.02400 |