Distributed Fundamentals based Conducting the Web Crawling Approaches and Types (Focused, Incremental, Distributed, Parallel, Hidden Web, Form Focused and Breadth First) Crawlers
Author:
Mehyadin Aska Ezadeen1, Abdulrahman Lozan M.2, Ahmed Sarkar Hasan3, Qashi Riyadh4
Affiliation:
1. Engeering Department, Technical College of Engineering , Duhok Polytechnic University , Duhok , Iraq 2. Information Technology Management., Technical College of Adminstration , Duhok Polytechnic University , Duhok , Iraq 3. Network Department, Technical College of Informatics , Sulaimani Polytechnic University , Sulaimani , Iraq 4. Vocational School Center 7, Electrical Engineering of the City of Leipzig , Laipzig , Germany
Abstract
Abstract
Over the last several years, there has been a significant rise in the number of people getting online and using the internet. Individual hypertext links are available, and any one of them may be used to get access to the resource. There is a variety of hypertext links available. It has been feasible to construct new websites as a result of the growth of crawlers, which has been facilitated by the rise in the number of people who use the internet. Web crawlers are highly evolved search engines that make it simpler for customers to get the information they are searching for on the internet. Web crawlers are also known as web crawlers. In a similar vein, these web crawlers have the potential to be used for more research endeavours in the months and years to come. Furthermore, the information that has been gathered may be used to detect and uncover any connections that are absent, as well as to assess the possibility for expansion inside complicated networks. This can be done by discovering any connections that are missing. The analysis of web crawlers is the primary topic of this study. Topics covered include the architecture of web crawlers, the many types of web crawlers, and the challenges that search engines have while using web crawlers.
Publisher
Walter de Gruyter GmbH
Reference51 articles.
1. M. M. Sadeeq, N. M. Abdulkareem, S. R. Zeebaree, D. M. Ahmed, A. S. Sami, and R. R. Zebari, “IoT and Cloud computing issues, challenges and opportunities: A review,” Qubahan Academic Journal, vol. 1, no. 2, pp. 1-7, 2021. 2. S. R. Zeebaree, H. M. Shukur, L. M. Haji, R. R. Zebari, K. Jacksi, and S. M. Abas, “Characteristics and analysis of hadoop distributed systems,” Technology Reports of Kansai University, vol. 62, no. 4, pp. 1555-1564, 2020. 3. P. Y. Abdullah, S. Zeebaree, K. Jacksi, and R. R. Zeabri, “An hrm system for small and medium enterprises (sme) s based on cloud computing technology,” International Journal of Research-GRANTHAALAYAH, vol. 8, no. 8, pp. 56-64, 2020. 4. J. Saeed and S. Zeebaree, “Skin lesion classification based on deep convolutional neural networks architectures,” Journal of Applied Science and Technology Trends, vol. 2, no. 01, pp. 41-51, 2021. 5. P. Y. Abdullah, S. Zeebaree, H. M. Shukur, and K. Jacksi, “HRM system using cloud computing for Small and Medium Enterprises (SMEs),” Technology Reports of Kansai University, vol. 62, no. 04, p. 04, 2020.
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