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The Algorithm Behind Page Rank of Search Engines
We are on the verge of the 21st century and the world of technological advances is continuously evolving, especially in the area of internet technology. One technology of the internet that has been evolving ever since was search engine. Going back in history, starting in 1990, the first search engine was developed. It was developed by a student in McGill University in Montreal in the name of Alan Emtage. He called the search engine he developed Archie, and was the grandfather of all search engines. Back then, Archie didn’t have the capabilities of today’s search engines but, it did provide some functionality for others to look around the internet if they knew the name of the files they are looking. Archie didn’t have the capacity for that time to index the content of text files. Then along came Gopher, a search engine developed after a year, in 1991, with the capability of indexing the content of text files. Since then, there are already of lot of search engines that are being developed. And search engines today have more capabilities and functionalities you can’t find from previous search engines. Technology indeed is constantly evolving. But what really is going on under the hood of these search engines? And how does it really work? In this article, we will try to decipher the technology behind these search engines and will look into a little bit of details of the algorithms behind them.
In one’s view point, we can appropriately imagine what a search engine does like keeping an index of all web pages, and when a user enters a keyword from the search bar, the engine then browses through its database and counts the number of occurrence of the keywords from the indexed web files. It will then return the web pages with the highest number of keywords found from its page and display it back to the user for viewing.
This is actually the scenario of the search engine in the early 1990s when it used the text based ranking systems. In this system, the pages are given relevance to the given query made by the users. But later on, problems with this approach were discovered. It did return results based from the query given by the user but the resulting web page is unexpected and the information is irrelevant from the user’s own perspective. A good example for this is to type a keyword “easymud”, and suppose we type it in the search bar and expected for it to return the auction website www.easymud.com. What will happen in this approach is that there maybe thousands or millions of websites containing the word “easymud”, and www.easymud.com may not be the one with the highest number of that word, most likely, the search engine will return a website that uses the word more often on their content which is not the online auction website we are anticipating. This is the problem that will be expected from using this approach and algorithm used by these early search engines.
Search engines effectiveness relies on its ability to return pages that are of significant relevance to the query given. It does not return so much value if the result is not as per user’s expectation and does not give them the relevant information that they need. There maybe sites with millions of web pages that included a particular word o phrase on its content; but some are more informative than the others. It is more reasonable to note and give more weight on the quality of the site’s content than the quantity of the word or phrase found on them. When users search for information, they will expect the web pages to be returned with so much relevance to the query they are searching. Don’t expect them to have the time and patience to browse for all the pages on the internet with that word or phrase and be the one to identify for the relevancy of the web pages. Search engines should have this capability and would be the one to recognize the relevancy of information as to the given query of a word or phrase. It is expected that search engine would return relevant pages to be displayed as per their rank. The first web page on that display means the most with significant relevance to the query. It will then be displayed from the top to bottom.
Since then, search engines have evolved and modern search engines right now, are more robust and versatile. It developed a method of providing best results based on the site’s ranking with the highest web page as the most relevant to the query. Page Rank algorithm then was developed. It became as the most known and most influential algorithm developed for computing with the relevance of web pages given more emphasis. This was developed by two graduate students of Stanford in the name of Sergey Brin and Larry Page and was first used in the search engine they invented to what is known right now as the Google search engine. It became a trademark for their company in 1998 and boosts their popularity to the top.
The design behind page ranking was that, the significance of a web page relies on the number of other pages link to it. For some illustration, suppose we have a web page of “Seo zip” and it provided a link to a web page of “Easy Mud”; this means that the web page of “Easy Mud” is somewhat very important and relevant to the content of the “Seo zip” page. And supposing there are more web pages pointing to the web page of “Easy Mud”, this is already a clear indication that the web page is of great importance. On the other side, if the web page of “Easy Mud” has only one backlink coming from the authoritative site www.datelot.com, we can therefore say that the said site transfers its authority to that of “Easy Mud”. In other words, the website www.datelot.com gives emphasis on the importance of the web page of “Easy Mud”. When we discuss the popularity or relevancy of a site, we can therefore calculate and assign ranking to its web pages based on the ranks of other web pages pointing to them. Based from this illustration alone, we can now clearly picture the algorithms and ideas behind these modern search engines.
Today, modern search engines are at the forefront of the internet, and are the number one tool used for searching relevant information on the entire web by professionals, students and other users alike. We may not know what this technology have in the future but we can be assured of its continuous evolution and will still be one of the facets of tools of the internet for the next centuries to come.
In one’s view point, we can appropriately imagine what a search engine does like keeping an index of all web pages, and when a user enters a keyword from the search bar, the engine then browses through its database and counts the number of occurrence of the keywords from the indexed web files. It will then return the web pages with the highest number of keywords found from its page and display it back to the user for viewing.
This is actually the scenario of the search engine in the early 1990s when it used the text based ranking systems. In this system, the pages are given relevance to the given query made by the users. But later on, problems with this approach were discovered. It did return results based from the query given by the user but the resulting web page is unexpected and the information is irrelevant from the user’s own perspective. A good example for this is to type a keyword “easymud”, and suppose we type it in the search bar and expected for it to return the auction website www.easymud.com. What will happen in this approach is that there maybe thousands or millions of websites containing the word “easymud”, and www.easymud.com may not be the one with the highest number of that word, most likely, the search engine will return a website that uses the word more often on their content which is not the online auction website we are anticipating. This is the problem that will be expected from using this approach and algorithm used by these early search engines.
Search engines effectiveness relies on its ability to return pages that are of significant relevance to the query given. It does not return so much value if the result is not as per user’s expectation and does not give them the relevant information that they need. There maybe sites with millions of web pages that included a particular word o phrase on its content; but some are more informative than the others. It is more reasonable to note and give more weight on the quality of the site’s content than the quantity of the word or phrase found on them. When users search for information, they will expect the web pages to be returned with so much relevance to the query they are searching. Don’t expect them to have the time and patience to browse for all the pages on the internet with that word or phrase and be the one to identify for the relevancy of the web pages. Search engines should have this capability and would be the one to recognize the relevancy of information as to the given query of a word or phrase. It is expected that search engine would return relevant pages to be displayed as per their rank. The first web page on that display means the most with significant relevance to the query. It will then be displayed from the top to bottom.
Since then, search engines have evolved and modern search engines right now, are more robust and versatile. It developed a method of providing best results based on the site’s ranking with the highest web page as the most relevant to the query. Page Rank algorithm then was developed. It became as the most known and most influential algorithm developed for computing with the relevance of web pages given more emphasis. This was developed by two graduate students of Stanford in the name of Sergey Brin and Larry Page and was first used in the search engine they invented to what is known right now as the Google search engine. It became a trademark for their company in 1998 and boosts their popularity to the top.
The design behind page ranking was that, the significance of a web page relies on the number of other pages link to it. For some illustration, suppose we have a web page of “Seo zip” and it provided a link to a web page of “Easy Mud”; this means that the web page of “Easy Mud” is somewhat very important and relevant to the content of the “Seo zip” page. And supposing there are more web pages pointing to the web page of “Easy Mud”, this is already a clear indication that the web page is of great importance. On the other side, if the web page of “Easy Mud” has only one backlink coming from the authoritative site www.datelot.com, we can therefore say that the said site transfers its authority to that of “Easy Mud”. In other words, the website www.datelot.com gives emphasis on the importance of the web page of “Easy Mud”. When we discuss the popularity or relevancy of a site, we can therefore calculate and assign ranking to its web pages based on the ranks of other web pages pointing to them. Based from this illustration alone, we can now clearly picture the algorithms and ideas behind these modern search engines.
Today, modern search engines are at the forefront of the internet, and are the number one tool used for searching relevant information on the entire web by professionals, students and other users alike. We may not know what this technology have in the future but we can be assured of its continuous evolution and will still be one of the facets of tools of the internet for the next centuries to come.
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