Araştırma Makalesi

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

Cilt: 4 Sayı: 1 30 Haziran 2023
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EN

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

Öz

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.

Anahtar Kelimeler

Destekleyen Kurum

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

Proje Numarası

KU AKMED 2020/P.1041.

Teşekkür

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.

Kaynakça

  1. 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
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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
  8. Luger, G. F. (2005). Artificial intelligence: structures and strategies for complex problem solving. Pearson education.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yazılım Mühendisliği (Diğer), Arkeoloji

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

12 Mayıs 2023

Yayımlanma Tarihi

30 Haziran 2023

Gönderilme Tarihi

2 Aralık 2022

Kabul Tarihi

4 Ocak 2023

Yayımlandığı Sayı

Yıl 2023 Cilt: 4 Sayı: 1

Kaynak Göster

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
AMA
1.Demir N, Boyoğlu CS, Kayıkcı D. A web scrapping and AI approach for archeologists to analyze the ancient cities. Cultural Heritage and Science. 2023;4(1):1-8. doi:10.58598/cuhes.1213426
Chicago
Demir, Nusret, Cem Sönmez Boyoğlu, ve Deniz Kayıkcı. 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.
EndNote
Demir N, Boyoğlu CS, Kayıkcı D (01 Haziran 2023) A web scrapping and AI approach for archeologists to analyze the ancient cities. Cultural Heritage and Science 4 1 1–8.
IEEE
[1]N. Demir, C. S. Boyoğlu, ve D. Kayıkcı, “A web scrapping and AI approach for archeologists to analyze the ancient cities”, Cultural Heritage and Science, c. 4, sy 1, ss. 1–8, Haz. 2023, doi: 10.58598/cuhes.1213426.
ISNAD
Demir, Nusret - Boyoğlu, Cem Sönmez - Kayıkcı, Deniz. “A web scrapping and AI approach for archeologists to analyze the ancient cities”. Cultural Heritage and Science 4/1 (01 Haziran 2023): 1-8. https://doi.org/10.58598/cuhes.1213426.
JAMA
1.Demir N, Boyoğlu CS, Kayıkcı D. A web scrapping and AI approach for archeologists to analyze the ancient cities. Cultural Heritage and Science. 2023;4:1–8.
MLA
Demir, Nusret, vd. “A web scrapping and AI approach for archeologists to analyze the ancient cities”. Cultural Heritage and Science, c. 4, sy 1, Haziran 2023, ss. 1-8, doi:10.58598/cuhes.1213426.
Vancouver
1.Nusret Demir, Cem Sönmez Boyoğlu, Deniz Kayıkcı. A web scrapping and AI approach for archeologists to analyze the ancient cities. Cultural Heritage and Science. 01 Haziran 2023;4(1):1-8. doi:10.58598/cuhes.1213426

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Online ISSN: 2757-9050