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Relevant bibliographies by topics / Web crawler behavior

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Academic literature on the topic 'Web crawler behavior'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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Journal articles on the topic "Web crawler behavior"

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张, 晓燕. "Research on the Crime of Web Crawler Behavior." Dispute Settlement 10, no. 02 (2024): 1130–37. http://dx.doi.org/10.12677/ds.2024.102155.

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Dikaiakos, Marios D., Athena Stassopoulou, and Loizos Papageorgiou. "An investigation of web crawler behavior: characterization and metrics." Computer Communications 28, no. 8 (2005): 880–97. http://dx.doi.org/10.1016/j.comcom.2005.01.003.

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Bai, Quan, Gang Xiong, Yong Zhao, and Longtao He. "Analysis and Detection of Bogus Behavior in Web Crawler Measurement." Procedia Computer Science 31 (2014): 1084–91. http://dx.doi.org/10.1016/j.procs.2014.05.363.

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Xing-Hua, Lu, Ye Wen-Quan, and Liu Ming-Yuan. "Personalized Recommendation Algorithm for Web Pages Based on Associ ation Rule Mining." MATEC Web of Conferences 173 (2018): 03020. http://dx.doi.org/10.1051/matecconf/201817303020.

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In order to improve the user ' s ability to access websites and web pages, according to the interest preference of the user, the personalized recommendation design is carried out, and the personalized recommendation model for web page visit is established to meet the personalized interest demand of the user to browse the web page. A webpage personalized recommendation algorithm based on association rule mining is proposed. Based on the semantic features of web pages, user browsing behavior is calculated by similarity computation, and web crawler algorithm is constructed to extract the semantic

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李, 朝阳. "Research on the Legal Regulation of Personal Information Tort of Web Crawler Behavior." E-Commerce Letters 13, no. 02 (2024): 3745–52. http://dx.doi.org/10.12677/ecl.2024.132458.

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Jing, Xu, Dong Jian He, Lin Sen Zan, Jian Liang Li, and Wang Yao. "Automatic Detection System of Web-Based Malware for Management-Type SaaS." Advanced Materials Research 129-131 (August 2010): 670–74. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.670.

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In management-type SaaS, user must be permitted to submit tenant’s business data on the SP's server, which may be embedded by the web-based malware. In this paper, we propose the automatic detecting method of web-based malware based on behavior analysis, which can make sure to meet the SLA by detecting the web-based malware actively. First, tenant’s update is downloaded to the bastion host by the web crawler. Second, it detect the behavior that tenant’s update is opened by IE. In order to break the malicious behavior during detecting, the IE has been injected in the DLL. Last, if the sensitive

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章, 徐南. "On the Application of Restrictions on the Characterization of Unfair Competition in Web Crawler Behavior." Dispute Settlement 10, no. 01 (2024): 245–50. http://dx.doi.org/10.12677/ds.2024.101035.

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Leithner, Manuel, and Dimitris E. Simos. "CHIEv." ACM SIGAPP Applied Computing Review 21, no. 1 (2021): 5–23. http://dx.doi.org/10.1145/3477133.3477134.

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Researchers and practitioners in the fields of testing, security assessment and web development seeking to evaluate a given web application often have to rely on the existence of a model of the respective system, which is then used as input to task-specific tools. Such models may include information on HTTP endpoints and their parameters, available user actions/event listeners and required assets. Unfortunately, this data is often unavailable in practice, as only rigorous development practices or manual analysis guarantee their existence and correctness. Crawlers based on static analysis have

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Muneeb Ahmed Farooqi, Muhammad Arslan Ashraf, and Muhammad Umer Shaukat. "Google Page Rank Site Structure Strategies for Marketing Web Pages." Journal of Computing & Biomedical Informatics 2, no. 02 (2021): 140–57. http://dx.doi.org/10.56979/202/2021/30.

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There are several Search Engines to categorize the web content and show us on base of our search query.These search engines are continuously visiting the pages/sites and gather the information using different techniques called crawling/spidering. On basis of daily content collection all search engines are managing their own indexes for searches.For every business there is a need to make its pages as most top rated/ranked pages by making structurally and content wise batter so that any crawler can easily crawl it and can rank it among the top 10 results.In this thesis only, structural behavior

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M., Bharathi, Aditya Sai Srinivas T., and Sri K.Teja. "From Pages to Citations: Optimizing Your Journal's Google Scholar Indexing Strategy." Journal of Advancement in Parallel Computing 7, no. 2 (2024): 13–19. https://doi.org/10.5281/zenodo.10862890.

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<em>Embark on a journey through the intricacies of Google Scholar indexing, where patience meets promise. This abstract navigates the path from compliance with inclusion guidelines to troubleshooting metadata discrepancies. Learn the art of optimizing article-level metadata and harnessing dedicated hosting platforms for enhanced indexing success. Discover strategies to mitigate indexing unpredictability and maintain consistency during website migrations. With insights into web crawler behavior and citation impact, unlock the gateway to expanded research accessibility. Join us in illuminating t

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Book chapters on the topic "Web crawler behavior"

1

Dikaiakos, Marios, Athena Stassopoulou, and Loizos Papageorgiou. "Characterizing Crawler Behavior from Web Server Access Logs." In E-Commerce and Web Technologies. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45229-4_36.

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Capriello, Antonella, and Piercarlo Rossi. "Spidering Scripts for Opinion Monitoring." In Advances in Data Mining and Database Management. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-4078-8.ch005.

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With the advent of Web 2.0 technologies, online forms of communication are rich sources of data to study socio-economic growth patterns and consumer behaviours. In this research field, the more robust development of data mining and opinion monitoring depends on fully automating data collection to monitor the evolution of customer opinions and preferences in real time. Although web crawlers or spiders can assist researchers in an innovative and effective way, this data collection approach could give rise to ethical concerns on the cost of web crawling processes and on data protection and privacy. With a focus on opinion monitoring, the chapter aims to discuss the ethical and legal issues of data mining in relation to spidering scripts. This contribution proposes a detailed analysis of the ethical and legal aspects of online data collection by comparing existing legislations. For illustrative purposes, a spidering software is presented to discuss its potential and explore ethical solutions in the data-mining sphere.

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Conference papers on the topic "Web crawler behavior"

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Ma, Haifei, Yilin Su, Lei Yang, and Yungui Chen. "Research about User Purchasing Behavior Analysis Based on Graph Convolutional Network and Web Crawler." In 2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2022. http://dx.doi.org/10.1109/iciscae55891.2022.9927619.

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Menshchikov, Alexander, Antonina Komarova, Yurij Gatchin, Anatoly Korobeynikov, and Nina Tishukova. "A study of different web-crawler behaviour." In 2017 20th Conference of Open Innovations Association (FRUCT). IEEE, 2017. http://dx.doi.org/10.23919/fruct.2017.8071322.

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Zhang, Lu, Zhan Bu, Zhiang Wu, and Jie Cao. "DGWC: Distributed and generic web crawler for online information extraction." In 2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC). IEEE, 2016. http://dx.doi.org/10.1109/besc.2016.7804487.

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