Abstract

For marketing purposes, Some Websites designers and administrators use illegal Search Engine Optimization (SEO) techniques to optimize the ranking of their Web pages and mislead the search engines. Some Arabic Web pages use both content and link features, to increase artificially the rank of their Web pages in the Search Engine Results Pages (SERPs). This study represents an enhancement to previous work in this field. It includes the design and implementation of an online Arabic Web spam detection system, based on algorithms and mathematical foundations, which can detect the Arabic content and link web spam depending on the tree of the spam detection conditions, beside depending on the user’s feedback through a custom Web browser. The users can participate in making the decision about any Web page, through their feedbacks, so they judge if the Arabic Web pages in the browser are relevant for their particular queries or not. The proposed system uses the extracted content and link features from Arabic Web pages to determine whether to label each Web page as a spam or as a non-spam. This system also attempts to learn from the user’s feedback to enhance automatically its performance. Statistical analysis is adopted in this study to evaluate the proposed system. Statistical Package for the Social Sciences (SPSS) software is used to evaluate this new system which considers the users feedbacks as dependent variables, while Arabic content and links features on the other hand are considered independent variables. The statistical analysis with the SPSS is used to apply a variety of tests, such as the test of the analysis of variance (ANOVA). ANOVA is used to show the relationships between the dependent and independent variables in the dataset, which leads to solving problems and building intelligent decisions and results.

Highlights

  • Arab Internet users suffer from two problems, the first problem is the low percentage of the Internet Arabic content, and the second problem is Arabic Web spam which leads Web search engines to refer to irrelevant Web pages

  • This study relies on a set of content and link Arabic Web spam conditions that have been used before, this study differs from its predecessors by involving the Web search engine users to assess the relevancy of Arabic Web pages rendered by Search Engine Results Pages (SERPs)

  • According to table 2, we can find that f test is 278.1157 with P-value equals to 0.006751, which is less than significant value of P-value (0.05), so we reject the null hypothesis, and accept the alternative hypothesis which asserts the relationship between the fifteen content and link Web spam features and the search engine ranking score

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Summary

Introduction

Arab Internet users suffer from two problems, the first problem is the low percentage of the Internet Arabic content, and the second problem is Arabic Web spam which leads Web search engines to refer to irrelevant Web pages. This study proposes an integrated system to reduce the Arabic content and link Web spam, and filter the search engines from these malicious Arabic web pages. This study relies on a set of content and link Arabic Web spam conditions that have been used before, this study differs from its predecessors by involving the Web search engine users to assess the relevancy of Arabic Web pages rendered by Search Engine Results Pages (SERPs). The proposed system allows users to use a synchronization technique, in which the users can browse the Arabic Web pages, and give their feedbacks assessment for each visited Web page under some security considerations and confidentiality. The use of a synchronization technique helps the proposed system to ensure that the submitted assessment is conducted by users not agents and robots

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