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In the following text I am trying to explain how I understand the topic. After having studied different sources I have drawn up this post.
The post topic is important for every blogger who wants to have a quality blog with quality content which attracts search engines and visitors. On the other hand, it is a great opportunity for writing a lively technical text for studying Tech English online. So, study the topic, study Tech English and write comments, which is the best way for practising the language.
Find necessary terminology in the Internet English Vocabulary.
Is a link analysis algorithm used by the Google Internet search engine. The algorithm assigns a numerical weighting to each element of hyperlinked documents on the World Wide Web with the purpose of “measuring” its relative importance within it. According to the Google theory if Page A links to Page B, then Page A is saying that Page B is an important page. If a page has more important links to it, then its links to other pages also become more important.
PageRank was developed at the Stanford University by Larry Page (thus the term PageRank is after him) and Sergey Brin as part of a research project about a new kind of a search engine. Now the “PageRank” is a trademark of Google. The PageRank process has been patented and assigned to the Stanford University, not to Google. Google has exclusive license rights on this patent from the university. The university received 1.8 million shares of Google in exchange for use of the patent; the shares were sold in 2005 for $336 million.
The first paper about the project, describing PageRank and the initial prototype of the Google search engine, was published in 1998: shortly after, Page and Brin founded the company Google Inc. Even if PageRank now is one of about 200 factors that determine the ranking of Google search results, it continues to provide the basis for all of Google web search tools.
Since 1996 a small search engine called “RankDex” designed by Robin Li has already been exploring a similar strategy for site-scoring and page ranking. This technology was patented by 1999 and was used later by Li when he founded Baidu in China.
Some basic information about PageRank
There is some basic information, which is needed to know for understanding PageRank.
First, PageRank is a number that only evaluates the voting ability of all incoming (inbound) links to a page.
Second, every unique page of a site that is indexed in Google has its own PageRank.
Third, internal site links interact in passing PageRank to other pages of the site.
Forth, the PageRank stands on its own. It is not tied in with the anchor text of links.
Fifth, there are two values of the PageRank that should be distinguished:
a. PageRank which you can get from the Internet Explorer toolbar (http://toolbar.google.com);
b. Actual or real PageRank that is used by Google for calculation of ranking web pages.
PageRank from the toolbar (sometimes called the Nominal Pagerank) has value from zero to ten. It is not very accurate information about site pages, but it is the only thing that gives you any idea about the value. It is updated approximately once every three months, more or less, while the real PageRank is calculated permanently as the Google bots crawl the web finding new web pages and new backlinks.
Thus, in the following text the term actual PageRank is employed to deal with the actual PageRank value stored by Google, and the term Toolbar PageRank concerns the evaluation of the value that you see on the Google Toolbar.
The Toolbar value is just a representation of the actual PageRank. While real PageRank is linear, Google uses a non-linear graph to show its representation. So on the toolbar, moving from a PageRank of 2 to a PageRank of 3 takes less of an increase than moving from a PageRank of 3 to a PageRank of 4.
This is illustrated by a comparison table (from PageRank Explained by Chris Ridings). The actual figures are kept secret, so for demonstration purposes some guessed figures were used:
If the actual PageRank is between
The Toolbar Shows
0.00000001 and 5
6 and 25
25 and 125
126 and 625
626 and 3125
3126 and 15625
15626 and 78125
78126 and 390625
390626 and 1953125
1953126 and infinity
The PageRank Algorithm
Lawrence Page and Sergey Brin have published two different versions of their PageRank algorithm in different papers.
First version (so called the Random Surfer Model) was published on the Stanford research paper titled The Anatomy of a Large-Scale Hypertextual Web Search Engine in 1998:
PR(A) = (1-d) + d(PR(T1)/C(T1) + … + PR(Tn)/C(Tn))
Where PR(A) is the PageRank of page A.
d is a damping factor, which is set between 0 and 1, nominally it is set to 0.85.
PR(T1) is the PageRank of a site page pointing to page A.
C(T1) is the number of outgoing links on page T1.
In the second version of the algorithm, the PageRank of page A is given as:
PR(A) = (1-d) / N + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))
Where N is the total number of all pages on the Web.
The first model is based on a very simple intuitive concept. The PageRank is put down as a model of user behaviour, where a surfer clicks on links at random. The probability that the surfer visits a page is the page PageRank. The probability that the surfer clicks on one link at the page is given by the number of links at the page. The probability at each page that the surfer will get bored and will jump to another random page is the damping factor d.
The second notation considers PageRank of a page the actual probability for a surfer reaching that page after clicking on many links. The PageRanks then form a probability distribution over web pages, so the sum of all pages PageRanks will be one.
As for calculating PageRank the calculations by means of its first model are easier to compute because the total number of web pages is disregarded.
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Composed by Galina Vitkova
SEO (Search engine optimisation)
Is the process of improving the visibility of a website or a web page or a blog in search engines. SEO aims to maximise profitable traffic from search engines to websites. In general, the more frequently a site appears in the search results list, the more visitors it will receive from the search engine users. Thus, technical communication among the search engine users, including bloggers will improve. Experience has shown that search engine traffic can make a firm success. Targeted visitors to a website or a blog may provide publicity, revenue, and exposure like no other. Investing in SEO, whether through time or finances, can have an exceptional rate of return.
SEO evaluates how search engines work, what people search for, the actual search terms typed into search engines. Moreover, SEO considers which search engines are preferred by their targeted audience. Optimising a website for searching may involve editing its content to increase its relevance to specific keywords and to remove barriers to the indexing activities of search engines (see Search engine essential information). Promoting a site to increase the number of backlinks, or inbound links, is another SEO task.
The success and popularity of a search engine is determined by its ability to produce the most relevant results to any given search. Otherwise, false search results could turn users to find other search sources. Therefore search engines with more complex ranking algorithms (which strongly affects SEO), taking into account additional factors have been evolved.
Google and its PageRank
The breakthrough idea behind Google was to analyse the relationships between the websites and pages to determine the relevancy of those pages to specific search queries. The Google founders, graduate students at Stanford University Larry Page and Sergey Brin, used this principle and developed a mathematical algorithm for a search engine to rate the prominence of web pages. The number calculated by the algorithm, has been named PageRank after Larry Page. PageRank estimates the likelihood that a given page will be reached by a user who randomly surfs the web and follows links from one page to another. In effect, this means that some links are stronger than others because a higher PageRank page is more likely to be reached by the random surfer.
Page and Brin founded Google using the developed algorithm for searching in 1998. Google attracted immediately the growing number of Internet users due to its simple design. In Google off-page factors (such as the PageRank and hyperlink analysis) as well as on-page factors (such as keyword frequency, meta tags, headings, links and site structure) were considered. It enables Google to avoid the kind of manipulation seen in search engines that only deliberated on-page factors for their rankings
Against improper SEO
Since the time of appearing ranking tools webmasters developed a great amount of link building instruments to influence search engine results within SEO. Many sites focused on exchanging, buying, and selling links, often on a massive scale which is not connected much with the spirit of SEO.
By 2004, search engines incorporated a wide range of undisclosed factors in their ranking algorithms to reduce the impact of link manipulation. The leading search engines, Google, Bing, and Yahoo, do not disclose their ranking algorithms, too.
Image via Wikipedia
In 2007, Google announced a campaign against paid links that transfer PageRank. On June 15, 2009, it took special measures to mitigate the effects of PageRank sculpting. In December 2009, Google announced it would be using the web search history of all its users in order to populate search results.
Google Instant, real-time-search, was introduced in late 2009 in an attempt to make search results more timely and relevant. Site administrators have spent months or even years optimising a website to increase search rankings. With the growth in popularity of social media sites and blogs the leading engines made changes to their algorithms to allow fresh content to rank quickly within the search results.
A variety of methods can increase the prominence of a webpage within the search results. Cross linking between pages of the same website or blog to provide more links to most important pages may improve its visibility. Writing content that includes frequently searched keyword phrases, so as to be relevant to a wide variety of search queries will tend to increase traffic. Updating content so as to keep search engines crawling back frequently can give additional weight to a site. Adding relevant keywords to web page meta data, including the title tag and meta description, will tend to improve the relevancy of a site search listings, thus increasing traffic. Several other techniques can help towards the page link popularity score. In any case, creating a useful, information-rich site, with pages that clearly and accurately describe your content should be one of the main goals of SEO.
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