Statistical analysis methods were selected to assess and analyze the results of the SEO and search engine visibility (SEV). Websites were analyzed by accessing the source code of their homepages through Google Chrome browser. The purpose of this research study is to analyze the influence of local geographical area, in terms of cultural values, and the effect of local society keywords in increasing Website visibility. SEO is the process of designing Webpages to optimize its potential to rank high on search engines, preferably on the first page of the results page. The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it is based on global in-link metric. We then compare the results of the normal search results (Sphider) and the results that come out of using K-Means and MPAPI. Each thread can connect to its own case connection takes place through messages not State transfer between Threads. Using this technique, search takes place in more one cluster in parallel. The paper decided to use the Message Passing Application Programming Interface(MPAPI) technique with the K-Means to solve the delay problem during search. As the size of data increases, the time used in searching is affected as search time increases to a great extent and the search process becomes slower. Upon conducting experiments, it is found that the algorithm produces better results without the clustering. This paper aims to improve the search time of search engines to the greatest extent using the K-Means Algorithm which does the Clustering of the database. The SEO can also be defined as the process affecting the visibility of a website or a webpage in search engines. The optimization targets different types of items such as images, videos, academic articles, etc. Search Engine Optimization (SEO) is the procedure used to improve the visibility of the results searched for on a free search engine for a website or a web page.
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