Research Analysis Of The Google Pagerank Algorithm

Definition of the Terminology

Discuss about the Research Analysis Of the Googls Pagerank Algorithm.

In this report the topic of the discussion is the chances of the Google delivering result that is not wanted as per the query of the user. In the report technologies that are used in the Google search engine is also discussed. There are various different algorithms that are applied for the search queries (Smith et al., 2018). Based on the technology and the algorithm the result is displayed. The algorithms and the technology are kept secret by the company as they do not want to disclose that. The Google search engine is very powerful tool. The critical thinking and the other aspects of the Google search engine is discussed below.

The Google is a very powerful tool in the market right now. The Google search engine is the most popular search engine among the all. There are many search engine in the market but the Google search engine is the best among all as the search engine produce almost accurate search and the relevant results according to the keywords (Lurie and Mustafaraj 2018).

The Google search engine provide all the information that a user is needed. The user makes their query on the search engine of the Google and the Google search engine then provide the results. To produce the more than near accurate many technology, search analysis and algorithm are used. The main algorithm that is used in the Google search engine is the PageRank algorithm (Multazam and Purnama 2015). The use of the PageRank algorithm makes the Google search engine better than the others. The ranking algorithm is also changed by the Google after that. The relevant elements are also now applied on the algorithm of PageRank. There are many rankings stored in the Google and to calculate the rankings Google installed huge amount servers. The server analyse all the content that is on the page or off the page. For each of the factor one algorithm is assigned (Pan 2015). The main job of these algorithms is to weight the pages and then assign their values. The assigned values are stored in the memory for the further use. When a user ask their query in the search engine then the another algorithm set analyse the stored assigned value for the relevance. If the weight of the query and the previously assigned values are same then the result will be displayed in the browser of the user (Gleich 2015).

Technology, Algorithm and Search Analysis Used in the Search Engine

The processing power of the Google servers are huge. The Google search engine provide the result very fast and so that much data cannot be written to the servers that are individuals. The most index of the Google is stored in the virtual memory. If not all then surely the data that are served to the users are stored in the virtual memory (Le and Kumar 2017).

There are many kinds of mapping that are done in the algorithm for the each of the query different mapping procedure is used and applied. Decentralization and redundancy is the main feature of the Google. For the each page there are multiple copies stored. The index of the Google is divided into multiple parts. The multiple indexes are store all over the Google. All the datacentre in the Google search engine are independent the tasks does not tends to overlap with each other (Banerjee and Choudhary 2017). The all the datacentre may be different from each other but the goal of the all data centre are same. Once in a month the data centre is updated by the Google. The each datacentre is updated by their own for that the number one ranked is not on the list of the top 30 in another data centers. At present the PageRank factor has moved in the other direction in the final calculation. There are lot of factors that are affecting the rankings of the Google. The result page of the search is impacted highly by the rearrangement of the rankings and the application of them.

The updating process of the Google is also changed as earlier they update once in a month but in the current time they have choose the technique of updating the index perceptually. As a user one can rarely see the updates that are made by the Google. But on an incremental level it happens and the update happens so quickly along with some major changes (Song et al., 2016). The Google is consist of various layers, the top layer is the only layer that we can see it on the browser only. The page we can see on the browser is implemented the result of the other lower layers of the Google search engine.

The Google search engine uses many of the programs that are automated and the programs are known as the spiders or crawlers. These automated programs are also used by the other search engines in the market. A large amount of keyword index is presented in the Google. The main feature of the Google is how Google ranks the keywords as a result. That determines the order of the result that in which order the Google search engine will display its results on the search engine results page or the SERP (Rai and Lal 2016). The trade mark algorithm of the Google is called PageRank, which will assign the particular web pages for their relevant score.

Display Procedures

The Google is the most famous search engine in the market right now. The Google provide more or less accurate enough results for the user query. The chance is less that the user will get unwanted result as per their query. The algorithm that are working for the Google that the result will be accurate or near about the keyword. As from the whole query the keywords are matched for the search and the desired result is generated as the outcome. The Google made the life of the human being easier as the all the information around the globe is placed in one place. Though the Google makes the human life convenient but it also faced several criticism as well. It also termed that the Google is making the human stupid. The human being are getting very much dependent on the platform even the easiest of question is also searched in the Google (Murrugarra, Miller and Mueller 2016). The user of the Google search engine eves query the dumbest of the questions as they think that they will get their all information in the Google. People even search that “How to search accurately in Google?” that makes no sense as people are being fully dependent and do not want to user their brains at all.

Conclusion:

From the above report it can be concluded that the chance of getting irrelevant result from the search engine of the Google is near impossible. The technology and the system analysis algorithms that are used by Google are the most updated and unique. The search engine of Google is more successful than the other search engines because of the ranking method that is used by the Google search engine. The technology, algorithm and the system analysis method of the Google search engine is discussed in the above report. The above report shows the technique that how Google results the relevant details as per the query of the users. The critical study is also discussed in the report which shows how Google is making the human life convenient and as well as making the humans stupid and internet dependent. The display procedure of search engine is also discussed in the above report. It is seen from the above report that the ranking algorithm that the Google search engine is used is the PageRank technology. A page rank technology store the all index and divided and store it to the servers when a user made the query the stored query is fetched and made the relevant comparison and shows the result as the outcome.  The processing power of the Google search engine is huge as the Google perform the task very fast. Google not only store all its information in the hard drive but the most of the data are stored in the virtual memory. The result that the Google produce is very fast and the Google store huge amount of data in its memory and data retrieval is very fast from this search engine.

Reference:

Smith, R., Kong, J., Ng, M., Larwrentschuk, N., Wickramesinghe, N. and Smart, P., 2018. Quality of colorectal cancer health information on the internet: a multilingual evaluation of the Google search engine.

Multazam, M. and Purnama, B.E., 2015. Influence Of Classified Ad On Google Page Rank And Number Of Visitors. Journal of Theoretical and Applied Information Technology, 81(2), p.174.Pan, B., 2015.

The power of search engine ranking for tourist destinations. Tourism Management, 47, pp.79-87.Gleich, D.F., 2015. PageRank beyond the Web. SIAM Review, 57(3), pp.321-363.Le, J. and Kumar, S., 2017.

PageRank–The Elite Algorithm: A Research Analysis of Google’s PageRank Algorithm on Controversial Search Terms And Bias in Search.Banerjee, A. and Choudhary, S., 2017.

Advanced Page Rank Algorithm with Semantics, In Links, Out Links and Google Analytics. arXiv preprint arXiv:1709.02858.Song, J., Pan, Z. and Rytsareva, I., VMware Inc, 2016. 

Pagerank algorithm lock analysis. U.S. Patent Application 14/634,502.Murrugarra, D., Miller, J. and Mueller, A.N., 2016.

Estimating Propensity Parameters Using Google PageRank and Genetic Algorithms. Frontiers in neuroscience, 10, p.513.Rai, P. and Lal, A., 2016. Google PageRank Algorithm: Markov Chain Model and Hidden Markov Model. International Journal of Computer Applications, 138(9).Lurie, E. and Mustafaraj, E., 2018, May.

Investigating the Effects of Google's Search Engine Result Page in Evaluating the Credibility of Online News Sources. In Proceedings of the 10th ACM Conference on Web Science (pp. 107-116). ACM.