Research Article
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A web scrapping and AI approach for archeologists to analyze the ancient cities

Year 2023, Volume: 4 Issue: 1, 1 - 8, 30.06.2023
https://doi.org/10.58598/cuhes.1213426

Abstract

Studies on machine learning have started to reach a level where we can save a great amount of time and labor by producing structures that can think as a human and have decisions. Deep learning, one of the methods of machine learning, is an artificial intelligence-training technique that can predict the outputs from the given dataset In this study, the use of web scraping technique was investigated to determine the potential of identifying ancient columns, which are one of the most important architectural elements of cultural heritage, by artificial intelligence. In this study, web scraping approach is presented as a digital data acquisition method for archaeology field to collect imagery datasets from web to analyze the ancient cities. For analysis, a free online, and easy-to-use tool ‘Amazon Rekognation’ is used for comparing the number of columns found in the scrapped images. For summarizing the research, simply, we have tried to get the answer the question from PC that ‘which site has the columns most, Perge, Xanthos or Phaselis?’. With this proposed approach, the archeologists can have a primarily knowledge about the sites they will study with use of operational tools for their further comprehensive research.

Supporting Institution

Koc University Suna & İnan Kıraç Research Center for Mediterranean Civilizations (AKMED)

Project Number

KU AKMED 2020/P.1041.

Thanks

This research has been supported by Koc University Suna & İnan Kıraç Research Center for Mediterranean Civilizations (AKMED) with Project Nr. KU AKMED 2020/P.1041.

References

  • Kintigh, K. W., Altschul, J. H., Beaudry, M. C., Drennan, R. D., Kinzig, A. P., Kohler, T. A., Limp, W. F., Maschner, H. D. G., Michener, W. K., Pauketat, T. R., Peregrine, P., Sabloff, J. A., Wilkinson, T. J., Wright, H. T., & Zeder, M. A. (2014). Grand challenges for archaeology. Proceedings of the National Academy of Sciences, 111(3), 879–880. https://doi.org/10.1073/PNAS.1324000111
  • Barceló, J. A. (2010, January). Computational intelligence in archaeology. State of the art. In Making History Interactive. Computer Applications and Quantitative Methods in Archaeology (CAA). Proceedings of the 37th International Conference (Vol. 11, p. 21). Williamsburg, Virginia, United States of America: Archaeopress.
  • Kan, M. H., Keskin, H., Demir, N., Selim, S., Aslan, E., & Güneş, N. (2022). A Preliminary Field Work on Digital Heritage and the Use of Virtual Reality for Cultural Heritage Management. Advances in Hospitality and Tourism Research (AHTR), 10(4), 625-645.
  • Korumaz, A. G., Dülgerler, O. N., & Yakar, M. (2011). Kültürel mirasin belgelenmesinde dijital yaklaşimlar. Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 26(3), 67-83.
  • Ulvi, A., Yakar, M., Yiğit, A., & Kaya, Y. (2019). The use of photogrammetric techniques in documenting cultural heritage: The Example of Aksaray Selime Sultan Tomb. Universal Journal of Engineering Science, 7(3), 64-73.
  • Karataş, L., Alptekin, A., & Yakar, M. (2022). Creating Architectural Surveys of Traditional Buildings with the Help of Terrestrial Laser Scanning Method (TLS) and Orthophotos: Historical Diyarbakır Sur Mansion. Advanced LiDAR, 2(2), 54-63.
  • Daems, D. (2020). A review and roadmap of online learning platforms and tutorials in digital archaeology. Advances in Archaeological Practice, 8(1), 87-92. https://doi.org/10.1017/aap.2019.47
  • Luger, G. F. (2005). Artificial intelligence: structures and strategies for complex problem solving. Pearson education.
  • Konar, A. (2006). Computational intelligence: principles, techniques and applications. Springer Science & Business Media.
  • Chuvieco, E., & Congalton, R. G. (1989). Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote sensing of Environment, 29(2), 147-159. https://doi.org/10.1016/0034-4257(89)90023-0
  • Russel, S., & Norvig, P. (2013). Artificial intelligence: a modern approach (Vol. 256). London: Pearson Education Limited.
  • AWS (2022). Machine Learning Image and Video Analysis- Amazon Rekognition. https://aws.amazon.com/rekognition/?nc1=h_ls
  • Muthukadan, B. (2022). Selenium with Python — Selenium Python Bindings 2 documentation. https://selenium-python.readthedocs.io/
  • Şahin, M. A., & Yakar, M. (2021). WebGIS technology and architectures. Advanced GIS, 1(1), 22-26.
  • Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web Scientific American, 284 (5), 34-43.
  • Graham, S., Huffer, D., & Blackadar, J. (2020). Towards a digital sensorial archaeology as an experiment in distant viewing of the trade in human remains on Instagram. Heritage, 3(2), 208-227.
  • https://ladvien.com/scraping-internet-for-magic-symbols/
  • Martini, W. (2013). Perge. The Encyclopedia of Ancient History.
  • Brandt, H. (2013). Phaselis. The Encyclopedia of Ancient History.
  • Des Courtils, J. (2013). La ville de Xanthos (Lycie) et son environnement.
Year 2023, Volume: 4 Issue: 1, 1 - 8, 30.06.2023
https://doi.org/10.58598/cuhes.1213426

Abstract

Project Number

KU AKMED 2020/P.1041.

References

  • Kintigh, K. W., Altschul, J. H., Beaudry, M. C., Drennan, R. D., Kinzig, A. P., Kohler, T. A., Limp, W. F., Maschner, H. D. G., Michener, W. K., Pauketat, T. R., Peregrine, P., Sabloff, J. A., Wilkinson, T. J., Wright, H. T., & Zeder, M. A. (2014). Grand challenges for archaeology. Proceedings of the National Academy of Sciences, 111(3), 879–880. https://doi.org/10.1073/PNAS.1324000111
  • Barceló, J. A. (2010, January). Computational intelligence in archaeology. State of the art. In Making History Interactive. Computer Applications and Quantitative Methods in Archaeology (CAA). Proceedings of the 37th International Conference (Vol. 11, p. 21). Williamsburg, Virginia, United States of America: Archaeopress.
  • Kan, M. H., Keskin, H., Demir, N., Selim, S., Aslan, E., & Güneş, N. (2022). A Preliminary Field Work on Digital Heritage and the Use of Virtual Reality for Cultural Heritage Management. Advances in Hospitality and Tourism Research (AHTR), 10(4), 625-645.
  • Korumaz, A. G., Dülgerler, O. N., & Yakar, M. (2011). Kültürel mirasin belgelenmesinde dijital yaklaşimlar. Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 26(3), 67-83.
  • Ulvi, A., Yakar, M., Yiğit, A., & Kaya, Y. (2019). The use of photogrammetric techniques in documenting cultural heritage: The Example of Aksaray Selime Sultan Tomb. Universal Journal of Engineering Science, 7(3), 64-73.
  • Karataş, L., Alptekin, A., & Yakar, M. (2022). Creating Architectural Surveys of Traditional Buildings with the Help of Terrestrial Laser Scanning Method (TLS) and Orthophotos: Historical Diyarbakır Sur Mansion. Advanced LiDAR, 2(2), 54-63.
  • Daems, D. (2020). A review and roadmap of online learning platforms and tutorials in digital archaeology. Advances in Archaeological Practice, 8(1), 87-92. https://doi.org/10.1017/aap.2019.47
  • Luger, G. F. (2005). Artificial intelligence: structures and strategies for complex problem solving. Pearson education.
  • Konar, A. (2006). Computational intelligence: principles, techniques and applications. Springer Science & Business Media.
  • Chuvieco, E., & Congalton, R. G. (1989). Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote sensing of Environment, 29(2), 147-159. https://doi.org/10.1016/0034-4257(89)90023-0
  • Russel, S., & Norvig, P. (2013). Artificial intelligence: a modern approach (Vol. 256). London: Pearson Education Limited.
  • AWS (2022). Machine Learning Image and Video Analysis- Amazon Rekognition. https://aws.amazon.com/rekognition/?nc1=h_ls
  • Muthukadan, B. (2022). Selenium with Python — Selenium Python Bindings 2 documentation. https://selenium-python.readthedocs.io/
  • Şahin, M. A., & Yakar, M. (2021). WebGIS technology and architectures. Advanced GIS, 1(1), 22-26.
  • Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web Scientific American, 284 (5), 34-43.
  • Graham, S., Huffer, D., & Blackadar, J. (2020). Towards a digital sensorial archaeology as an experiment in distant viewing of the trade in human remains on Instagram. Heritage, 3(2), 208-227.
  • https://ladvien.com/scraping-internet-for-magic-symbols/
  • Martini, W. (2013). Perge. The Encyclopedia of Ancient History.
  • Brandt, H. (2013). Phaselis. The Encyclopedia of Ancient History.
  • Des Courtils, J. (2013). La ville de Xanthos (Lycie) et son environnement.
There are 20 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other), Archaeology
Journal Section Research Articles
Authors

Nusret Demir 0000-0002-8756-7127

Cem Sönmez Boyoğlu 0000-0001-9367-7931

Deniz Kayıkcı 0000-0002-1311-4272

Project Number KU AKMED 2020/P.1041.
Early Pub Date May 12, 2023
Publication Date June 30, 2023
Published in Issue Year 2023 Volume: 4 Issue: 1

Cite

APA Demir, N., Boyoğlu, C. S., & Kayıkcı, D. (2023). A web scrapping and AI approach for archeologists to analyze the ancient cities. Cultural Heritage and Science, 4(1), 1-8. https://doi.org/10.58598/cuhes.1213426

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