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

Nusret Demir; Cem Sönmez Boyoğlu; Deniz Kayıkcı

Makale detayları

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

Yazarlar:

Nusret Demir | Cem Sönmez Boyoğlu | Deniz Kayıkcı

Yayıncı:

Mersin University

Ana Başlıklar:

Software Engineering (Other) | Archaeology

Dergi:

Cultural Heritage and Science Vol.4 Issue 1, pp.1-8

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001289685

pISSN:

2757-9050

Anahtar kelimeler:

Özet:

 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.

 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.

 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.

 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.

Makale detayları

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

Yazarlar:

Nusret Demir | Cem Sönmez Boyoğlu | Deniz Kayıkcı

Yayıncı:

Mersin University

Ana Başlıklar:

Software Engineering (Other) | Archaeology

Dergi:

Cultural Heritage and Science Vol.4 Issue 1, pp.1-8

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001289685

pISSN:

2757-9050

Digital Cultural Heritage

Semantic Web

Web Scrapping

Deep Learning

Archaeology

Sayı

Makale detayları

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

Yazarlar: Nusret Demir | Cem Sönmez Boyoğlu | Deniz Kayıkcı

Yayıncı: Mersin University

Ana Başlıklar: Software Engineering (Other) | Archaeology

Dergi: Cultural Heritage and Science Vol.4 Issue 1, pp.1-8

Belge Tipi: Makale

Yayın Tarihi: 6/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001289685

pISSN: 2757-9050

Digital Cultural Heritage

Semantic Web

Web Scrapping

Deep Learning

Archaeology

Sayı

Yazarlar:

Nusret Demir | Cem Sönmez Boyoğlu | Deniz Kayıkcı

Yayıncı:

Mersin University

Ana Başlıklar:

Software Engineering (Other) | Archaeology

Dergi:

Cultural Heritage and Science Vol.4 Issue 1, pp.1-8

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001289685

pISSN:

2757-9050