An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach

In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most signif...

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Autores principales:	Asim Shahzad, Nazri Mohd Nawi, Muhammad Zubair Rehman, Abdullah Khan
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/274c41712f3d4001b9f65cdbbcac9d18
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id	oai:doaj.org-article:274c41712f3d4001b9f65cdbbcac9d18
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spelling	oai:doaj.org-article:274c41712f3d4001b9f65cdbbcac9d182021-11-29T00:55:27ZAn Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach1099-052610.1155/2021/6625739https://doaj.org/article/274c41712f3d4001b9f65cdbbcac9d182021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6625739https://doaj.org/toc/1099-0526In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.Asim ShahzadNazri Mohd NawiMuhammad Zubair RehmanAbdullah KhanHindawi-WileyarticleElectronic computers. Computer scienceQA75.5-76.95ENComplexity, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electronic computers. Computer science QA75.5-76.95
spellingShingle	Electronic computers. Computer science QA75.5-76.95 Asim Shahzad Nazri Mohd Nawi Muhammad Zubair Rehman Abdullah Khan An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
description	In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.
format	article
author	Asim Shahzad Nazri Mohd Nawi Muhammad Zubair Rehman Abdullah Khan
author_facet	Asim Shahzad Nazri Mohd Nawi Muhammad Zubair Rehman Abdullah Khan
author_sort	Asim Shahzad
title	An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
title_short	An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
title_full	An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
title_fullStr	An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
title_full_unstemmed	An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
title_sort	improved framework for content- and link-based web-spam detection: a combined approach
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/274c41712f3d4001b9f65cdbbcac9d18
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An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach

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