The Green Lauren Algorithm 2.0 is probably just a code of action for manual work.

Source: Internet
Author: User
Tags date manual domain domain name sub domain

The first two days to see Baidu Webmaster platform Lee released on July 5, Green Luo algorithm 2.0 interpretation, the article explains the Green Luo algorithm 2.0 for the focus of the target and punish the way,

  

Finally, a number of software publishing stations and soft text trading platform, including more well-known links and soft Wen trading platform Ali slightly and very common soft Wen publishing station thousand Long network. So, what exactly is the green Lauren Algorithm 2.0? How will the operation of the algorithm affect the webmaster? I would also like to say my opinion.

The promotion of the new website as well as various network marketing methods can not be separated from soft text. Through a large number of high-weight high PR website published soft text can quickly let netizens understand to promote content, quickly expand the promotion of content awareness. But the search engine work is a bad influence, when a large number of ads soft text flooded with search engines, users can no longer use the search engine simply and quickly to find what they want, when the user experience appears so bad, will directly lead to user dissatisfaction or even loss.

In the face of such a situation, Baidu's approach is to these soft text publishing stations related to the snapshot clear, then, well-known soft Wen trading station and soft text publishing station can manually join the blacklist, but more unknown?

This can only rely on the robot to work, shouldering such a task is the Green Luo algorithm. The task of the Green Robin algorithm was glorious and arduous. Before the punishment, the Green Luo algorithm needs to automatically identify which articles belong to the soft text, which site and the soft text is closely related to determine the punishment object can be punished.

Baidu Webmaster platform in the bulletin shows that the object of punishment include: soft Wen trading platform, soft paper publishing station, soft paper revenue station three categories, and the penalty is to clean up the snapshot results, serious point of direct reduction of the right to deal with or shielding the domain name, the original is Baidu news source is directly clean out Baidu news source, The most serious is the use of a large number of sub domain names to publish soft text, such a situation will block the entire primary domain name.

I checked a few Baidu announced the penalty site domain name, these domain names in Baidu Search does not have a snapshot, Ali slightly trading platform has been K.

In fact, said so much is nonsense, webmaster are most concerned about is the Green Luo algorithm 2.0 is how to work, is how to determine whether a website is a soft paper trading platform or soft text publishing station.

I think, the identification of soft Wen trading platform is not difficult, because the soft text trading platform Web page must contain and soft text trading related keywords, I believe that the green Luo algorithm can easily put such a platform list out. However, the soft Wen publishing station and the soft text revenue station These two kinds of difficulty has increased, the so-called soft text publishing station is to meet the task weak text of the site, and the soft text income station is the website of the money and weak text.

The reason why the two sites are difficult to identify is that their relationships are very similar to those of the Web site and contributors.

Soft Wen Trading: Website A pays to site B, then publishes articles in site B and leaves a link to site A.

Submission Process: Site A contribution to the site B, site B audit after the post and leave a link to site A.

In simple contrast, we would be surprised to find that the relationship between them is so similar. So how does the Green Lauren Algorithm 2.0 find and differentiate them? Let me make a guess, and guess how the green Rose Algorithm 2.0 works.

Method One: The following are the clues. Use the most familiar method of search engine, through the link of soft Wen trading station, to find the owner and the West home.

Method Two: Content recognition. Through the similarity of the Web page recognition, to determine whether the site has a large number of similar articles in order to judge the contribution or soft text.

I am not Baidu, I do not understand Baidu. These two methods are only my guess, it is difficult to make a good guess. As far as I understand the soft Wen trading station is very few can see the site link, and some are to be logged in order to see, and the content of the identification is not to mention, Baidu original Origin algorithm has let us these small webmaster enough to worry about, do not believe? A diagram shows the origin of Baidu algorithm.

You may not see anything on the map, give you a reminder, look at the original logo (the date before the snapshot profile) and the snapshot time. "Micro-letter no app concept of the public platform dream?" I'm sorry, people don't buy your account. This article I posted on June 23 in the blog, and then contributed to a number of Web sites, the Internet some things this site I also voted. However, Baidu original logo declined to my snapshot results, but something about the internet is something on this site. Even more ironic is that my article snapshot date is June 23, and some of the Internet is on 24th only to pass my submission, so the snapshot date is June 24.

My blog post snapshot date is June 23, and some of the internet things are on June 24, that is, the first to enter the Baidu index database is my dream blog, rather than some of the internet, the funny thing is that the original logo fell on the internet some things on the snapshot.

What does that mean? Is it the website that gets the invitation to mark the original? Or is it the wrong algorithm?

Baidu origin algorithm of the working way is really incredible. As for the green Lauren Algorithm 2.0, no comment is made. This living example is enough to explain Baidu's lack of content-recognition algorithms, and the green-Lauren algorithm 2.0 may be just a code of action for manual work.

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