TrustRank algorithm TrustRank algorithm originally came from a joint research of Stanford University and Yahoo in 2004, aiming at detecting spam websites, and applied for a patent in 2006. The inventor of TrustRank algorithm also published a special PDF file to illustrate the application of TrustRank algorithm. Interested readers can download PDF files at the following websites:
TrustRank algorithm was not put forward by Google, but because Google has the largest market share and TrustRank is also a very important factor in Google ranking, some people mistakenly think that TrustRank was put forward by Google. What is even more confusing is that Google once applied for TrustRank as a trademark, but TrustRank in TrustRank trademark refers to Google's method of detecting websites containing malicious code, not trustrank in ranking algorithm.
Based on this assumption, if we can select 100% credible websites, these websites have the highest TrustRank, and the websites with the highest trustrank are connected with slightly lower trustrank, but they will also be higher. Similarly, the trust of the third-level websites linked by the second-level trusted websites continues to decline. For various reasons, good websites will inevitably receive some junk websites. However, the closer the click distance from the first-level website is, the higher the trustrank will be. The farther away from the click distance of the first-level website, the lower the trustrank will be. In this way, the trustrank algorithm can calculate the corresponding trustrank for all websites, and the farther away from the first-level website, the greater the possibility of becoming a spam network.
PageRankPageRank, that is, web page ranking, is an algorithm used by Google to identify the ranking or importance of web pages.
The earliest search engines used the method of directory classification, that is, manually classifying web pages to sort out high-quality websites.
With the rapid increase of the number of web pages, this method is obviously impossible to achieve. As a result, the search engine has entered the era of text retrieval, that is, by calculating the correlation between the user's query sentence and the content of the web page, the search results are returned. For example, the input search words and files are converted into vectors by vector space model, and the correlation is measured by calculating the deviation degree of the included angle between the two vectors (generally using cosine distance). Although this method can handle a large number of web pages, the effect is not very good, for example, there are some cheating behaviors: some web pages repeatedly dump certain keywords to make their search rank high.
As a result, Larry Page and sergey brin, two founders of Google, who were graduate students at Stanford University, began to study the ranking of web pages. Inspired by the evaluation method of the importance of academic papers (citation times), they put forward PageRank algorithm.
The core idea of PageRank is actually very simple, which can be summarized as follows:
If a webpage is linked by many other webpages, it means that this webpage is very important, and its PageRank value will be higher accordingly.
If a page with a high PageRank value is linked to another page, the PageRank value of that page will increase accordingly.
HillTop algorithm HillTop is a patent of search engine result ranking, which was obtained by Bharat, an engineer of Google, on 200 1. Google's sorting rules are constantly changing, but the biggest change is the optimization based on HillTop algorithm.