Academic literature on the topic 'Spamdexing'

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Journal articles on the topic "Spamdexing"

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Polanski, Paul Przemyslaw. "Spam, spamdexing and regulation of internet advertising." International Journal of Intellectual Property Management 2, no. 2 (2008): 139. http://dx.doi.org/10.1504/ijipm.2008.019337.

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S.K., Jayanthi, and Sasikala S. "NLSDF FOR BOOSTING THE RECITAL OF WEB SPAMDEXING CLASSIFICATION." ICTACT Journal on Soft Computing 07, no. 01 (2016): 1324–31. http://dx.doi.org/10.21917/ijsc.2016.0183.

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Jayanthi, S. K., S. Sasikala, and J. P. Vishnupriya. "Comprehensive Evaluation of Machine Learning Techniques and Novel Features for Web Link Spamdexing Detection." ScieXplore: International Journal of Research in Science 1, no. 2 (2014): 98. http://dx.doi.org/10.15613/sijrs/2014/v1i2/67548.

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Ashish, Chandra Mohammad Suaib and Dr. Rizwan Beg. "GOOGLE SEARCH ALGORITHM UPDATES AGAINST WEB SPAM." Informatics Engineering, an International Journal (IEIJ) 03, mar (2015): 01–10. https://doi.org/10.5121/ieij.2015.3101.

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With the search engines' increasing importance in people's life, there are more and more attempts to illegitimately influence page ranking by means of web spam. Web spam detection is becoming a major challenge for internet search providers. The Web contains a huge number of profit-seeking ventures that are attracted by the prospect of reaching millions of users at a very low cost. There is an economic incentive for manipulating search engine’s listings by creating otherwise useless pages that score high ranking in the search results. Such manipulation is widespread in the industry. There is a large gray area between the Ethical SEO and the Unethical SEO i.e. spam industry. SEO services range from making web pages indexed, to the creation of millions of fake web pages to deceive search engine ranking algorithms. Today's search engines need to adapt their ranking algorithms continuously to mitigate the effect of spamming tactics on their search results. Search engine companies keep their search ranking algorithms and ranking features secret to protect their ranking system from gaming by spam tactics. We tried to collect here all the Google's search algorithm updates from different sources which are against web spam.
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Shahzad, Asim, Hairulnizam Mahdin, and Nazri Mohd. "An Improved Framework for Content-based Spamdexing Detection." International Journal of Advanced Computer Science and Applications 11, no. 1 (2020). http://dx.doi.org/10.14569/ijacsa.2020.0110151.

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Jayanthi, S. K., and S. Sasikala. "Clique-Attacks Detection in Web Search Engine for Spamdexing using K-Clique Percolation Technique." International Journal of Machine Learning and Computing, 2012, 648–53. http://dx.doi.org/10.7763/ijmlc.2012.v2.207.

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Dissertations / Theses on the topic "Spamdexing"

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Zuze, Herbert. "The crossover point between keyword rich website text and spamdexing." Thesis, Cape Peninsula University of Technology, 2011. http://hdl.handle.net/20.500.11838/1767.

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Thesis Submitted in fulfilment of the requirements for the degree MAGISTER TECHNOLOGIAE In BUSINESS INFORMATION SYSTEMS in the FACULTY OF BUSINESS at the CAPE PENINSULA UNIVERSITY OF TECHNOLOGY 2011<br>With over a billion Internet users surfing the Web daily in search of information, buying, selling and accessing social networks, marketers focus intensively on developing websites that are appealing to both the searchers and the search engines. Millions of webpages are submitted each day for indexing to search engines. The success of a search engine lies in its ability to provide accurate search results. Search engines’ algorithms constantly evaluate websites and webpages that could violate their respective policies. For this reason some websites and webpages are subsequently blacklisted from their index. Websites are increasingly being utilised as marketing tools, which result in major competition amongst websites. Website developers strive to develop websites of high quality, which are unique and content rich as this will assist them in obtaining a high ranking from search engines. By focusing on websites of a high standard, website developers utilise search engine optimisation (SEO) strategies to earn a high search engine ranking. From time to time SEO practitioners abuse SEO techniques in order to trick the search engine algorithms, but the algorithms are programmed to identify and flag these techniques as spamdexing. Search engines do not clearly explain how they interpret keyword stuffing (one form of spamdexing) in a webpage. However, they regard spamdexing in many different ways and do not provide enough detail to clarify what crawlers take into consideration when interpreting the spamdexing status of a website. Furthermore, search engines differ in the way that they interpret spamdexing, but offer no clear quantitative evidence for the crossover point of keyword dense website text to spamdexing. Scholars have indicated different views in respect of spamdexing, characterised by different keyword density measurements in the body text of a webpage. This raised several fundamental questions that form the basis of this research. This research was carried out using triangulation in order to determine how the scholars, search engines and SEO practitioners interpret spamdexing. Five websites with varying keyword densities were designed and submitted to Google, Yahoo! and Bing. Two phases of the experiment were done and the results were recorded. During both phases almost all of the webpages, including the one with a 97.3% keyword density, were indexed. The aforementioned enabled this research to conclusively disregard the keyword stuffing issue, blacklisting and any form of penalisation. Designers are urged to rather concentrate on usability and good values behind building a website. The research explored the fundamental contribution of keywords to webpage indexing and visibility. Keywords used with or without an optimum level of measurement of richness and poorness result in website ranking and indexing. However, the focus should be on the way in which the end user would interpret the content displayed, rather than how the search engine would react towards the content. Furthermore, spamdexing is likely to scare away potential clients and end users instead of embracing them, which is why the time spent on spamdexing should rather be used to produce quality content.
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Book chapters on the topic "Spamdexing"

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Kulkarni, Apeksha, Devansh Solani, Preet Sanghavi, Achyuth Kunchapu, M. Vijayalakshmi, and Sindhu Nair. "Discernment of Unsolicited Internet Spamdexing Using Graph Theory." In Inventive Systems and Control. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1012-8_4.

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"Spamdexing." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_3636.

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Conference papers on the topic "Spamdexing"

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Jayanthi, S. K., and S. Sasikala. "WESPACT: — Detection of web spamdexing with decision trees in GA perspective." In 2012 International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME). IEEE, 2012. http://dx.doi.org/10.1109/icprime.2012.6208376.

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