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

Year 2023, Volume: 4 Issue: 1, 1 - 8, 30.06.2023

Nusret Demir , Cem Sönmez Boyoğlu , Deniz Kayıkcı

https://doi.org/10.58598/cuhes.1213426

Cited By: 1

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.

Keywords

Digital Cultural Heritage, Semantic Web, Web Scrapping, Deep Learning, Archaeology

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.

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