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(2022). <i>Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu?</i> Jahrestagung des Verbands Digital Humanities im deutschsprachigen Raum, Potsdam.","bibtex":"@inproceedings{Altenhöner_Dieckmann_Münzmay_Richts-Matthaei_Röwenstrunk_Stellmacher_Pratschke_Primavesi_Schulz_2022, title={Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu?}, author={Altenhöner, Reinhard and Dieckmann, Lisa and Münzmay, Andreas and Richts-Matthaei, Kristina and Röwenstrunk, Daniel and Stellmacher, Martha and Pratschke, Margarete and Primavesi, Patrick and Schulz, Christoph}, year={2022} }","mla":"Altenhöner, Reinhard, et al. <i>Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu?</i> 2022.","short":"R. Altenhöner, L. Dieckmann, A. Münzmay, K. Richts-Matthaei, D. Röwenstrunk, M. Stellmacher, M. Pratschke, P. Primavesi, C. Schulz, in: 2022.","ieee":"R. Altenhöner <i>et al.</i>, “Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu?,” presented at the Jahrestagung des Verbands Digital Humanities im deutschsprachigen Raum, Potsdam, 2022.","chicago":"Altenhöner, Reinhard, Lisa Dieckmann, Andreas Münzmay, Kristina Richts-Matthaei, Daniel Röwenstrunk, Martha Stellmacher, Margarete Pratschke, Patrick Primavesi, and Christoph Schulz. “Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu?,” 2022.","ama":"Altenhöner R, Dieckmann L, Münzmay A, et al. Kultur – Daten – Kuratierung: Was Speichern Wir Und Wozu? In: ; 2022."}},{"department":[{"_id":"195"},{"_id":"196"}],"user_id":"77066","_id":"27506","language":[{"iso":"eng"}],"keyword":["Explainable Artificial Intelligence (XAI)","Regression Activation Maps","Real Estate Appraisal","Convolutional Block Attention Module","Computer Vision"],"publication":"55th Annual Hawaii International Conference on System Sciences (HICSS-55)","type":"conference","status":"public","abstract":[{"text":"Explainability for machine learning gets more and more important in high-stakes decisions like real estate appraisal. While traditional hedonic house pricing models are fed with hard information based on housing attributes, recently also soft information has been incorporated to increase the predictive performance. This soft information can be extracted from image data by complex models like Convolutional Neural Networks (CNNs). However, these are intransparent which excludes their use for high-stakes financial decisions. To overcome this limitation, we examine if a two-stage modeling approach can provide explainability. We combine visual interpretability by Regression Activation Maps (RAM) for the CNN and a linear regression for the overall prediction. Our experiments are based on 62.000 family homes in Philadelphia and the results indicate that the CNN learns aspects related to vegetation and quality aspects of the house from exterior images, improving the predictive accuracy of real estate appraisal by up to 5.4%.","lang":"eng"}],"date_created":"2021-11-17T07:08:15Z","author":[{"first_name":"Jan-Peter","last_name":"Kucklick","id":"77066","full_name":"Kucklick, Jan-Peter"}],"date_updated":"2022-01-06T06:57:40Z","oa":"1","conference":{"end_date":"2022-01-07","location":"Virtual","name":"Hawaii International Conference on System Science (HICSS)","start_date":"2022-01-03"},"main_file_link":[{"url":"https://scholarspace.manoa.hawaii.edu/bitstream/10125/79519/0149.pdf","open_access":"1"}],"title":"Visual Interpretability of Image-based Real Estate Appraisal","citation":{"chicago":"Kucklick, Jan-Peter. “Visual Interpretability of Image-Based Real Estate Appraisal.” In <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>, 2022.","ieee":"J.-P. Kucklick, “Visual Interpretability of Image-based Real Estate Appraisal,” presented at the Hawaii International Conference on System Science (HICSS), Virtual, 2022.","ama":"Kucklick J-P. Visual Interpretability of Image-based Real Estate Appraisal. In: <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>. ; 2022.","apa":"Kucklick, J.-P. (2022). Visual Interpretability of Image-based Real Estate Appraisal. <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>. Hawaii International Conference on System Science (HICSS), Virtual.","bibtex":"@inproceedings{Kucklick_2022, title={Visual Interpretability of Image-based Real Estate Appraisal}, booktitle={55th Annual Hawaii International Conference on System Sciences (HICSS-55)}, author={Kucklick, Jan-Peter}, year={2022} }","mla":"Kucklick, Jan-Peter. “Visual Interpretability of Image-Based Real Estate Appraisal.” <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>, 2022.","short":"J.-P. Kucklick, in: 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022."},"year":"2022"},{"oa":"1","date_updated":"2022-01-06T06:57:40Z","author":[{"first_name":"Tim","full_name":"Heuwinkel, Tim","last_name":"Heuwinkel"},{"id":"77066","full_name":"Kucklick, Jan-Peter","last_name":"Kucklick","first_name":"Jan-Peter"},{"first_name":"Oliver","id":"72849","full_name":"Müller, Oliver","last_name":"Müller"}],"date_created":"2021-11-17T07:12:03Z","title":"Using Geolocated Text to Quantify Location in Real Estate Appraisal","main_file_link":[{"open_access":"1","url":"https://scholarspace.manoa.hawaii.edu/bitstream/10125/80039/0561.pdf"}],"conference":{"end_date":"2022-01-07","location":"Virtual","name":"Hawaii International Conference on System Science (HICSS)","start_date":"2022-01-03"},"year":"2022","citation":{"apa":"Heuwinkel, T., Kucklick, J.-P., &#38; Müller, O. (2022). Using Geolocated Text to Quantify Location in Real Estate Appraisal. <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>. Hawaii International Conference on System Science (HICSS), Virtual.","bibtex":"@inproceedings{Heuwinkel_Kucklick_Müller_2022, title={Using Geolocated Text to Quantify Location in Real Estate Appraisal}, booktitle={55th Annual Hawaii International Conference on System Sciences (HICSS-55)}, author={Heuwinkel, Tim and Kucklick, Jan-Peter and Müller, Oliver}, year={2022} }","mla":"Heuwinkel, Tim, et al. “Using Geolocated Text to Quantify Location in Real Estate Appraisal.” <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>, 2022.","short":"T. Heuwinkel, J.-P. Kucklick, O. Müller, in: 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022.","ama":"Heuwinkel T, Kucklick J-P, Müller O. Using Geolocated Text to Quantify Location in Real Estate Appraisal. In: <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>. ; 2022.","ieee":"T. Heuwinkel, J.-P. Kucklick, and O. Müller, “Using Geolocated Text to Quantify Location in Real Estate Appraisal,” presented at the Hawaii International Conference on System Science (HICSS), Virtual, 2022.","chicago":"Heuwinkel, Tim, Jan-Peter Kucklick, and Oliver Müller. “Using Geolocated Text to Quantify Location in Real Estate Appraisal.” In <i>55th Annual Hawaii International Conference on System Sciences (HICSS-55)</i>, 2022."},"_id":"27507","user_id":"77066","department":[{"_id":"195"}],"keyword":["Real Estate Appraisal","Text Regression","Natural Language Processing (NLP)","Location Intelligence","Wikipedia"],"language":[{"iso":"eng"}],"type":"conference","publication":"55th Annual Hawaii International Conference on System Sciences (HICSS-55)","abstract":[{"lang":"eng","text":"Accurate real estate appraisal is essential in decision making processes of financial institutions, governments, and trending real estate platforms like Zillow. One of the most important factors of a property’s value is its location. However, creating accurate quantifications of location remains a challenge. While traditional approaches rely on Geographical Information Systems (GIS), recently unstructured data in form of images was incorporated in the appraisal process, but text data remains an untapped reservoir. Our study shows that using text data in form of geolocated Wikipedia articles can increase predictive performance over traditional GIS-based methods by 8.2% in spatial out-of-sample validation. A framework to automatically extract geographically weighted vector representations for text is established and used alongside traditional structural housing features to make predictions and to uncover local patterns on sale price for real estate transactions between 2015 and 2020 in Allegheny County, Pennsylvania."}],"status":"public"}]