Google SEO workers can only understand the operating principle of the increasingly intelligent Google search engine if they first understand the topic model and semantic connection of the Google search engine, so that they can carry out Google SEO optimization on the website in a targeted manner.
search engines, especially google, capable of understanding people's intentions quite well, although not yet very precisely. So, how do search engines do this? Next, Jiexin Network Marketing Agency will explain in detail for you.
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This involves Topic Modeling and Semantic Connectivity. These two words sound difficult to understand, but in fact, they are an important part of helping us understand how search engines operate, and they are important for SEO. Some aspects have a great influence. Therefore, it is necessary to understand these two words first.
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In fact, search engines have a smarter understanding of the words and phrases people use to search. For example, when searching for the word "Super Mario", people may think that only webpages with "Super Mario" as the title can be searched, but in fact, as long as the title or article contains "Super Mario", all webpages can be searched. And that's the real purpose of SEO, to give searchers the best answers of all. But search engines are actually far smarter than that.
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Another great example is Google's movie search. For example, Google "a movie about a dude" and you'll see "The Big Lebowski" come up first. So how does Google know? Google combined "movies" and "Playboy" and found that the movie "The Big Lebowski" was most closely related to both. And this movie is exactly what users are looking for, and no website will have "a movie about a dude" as the title.
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Still take "Super Mario" as an example, "Super Mario" will involve many related words or phrases. Therefore, the search engine understands the word more semantically, and it may first associate the word with "Mario", then "Luigi", and then "King Bowser", which is the A villainous turtle with a back full of nails.
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From the above examples, we can see that search engines have their own set of topic model algorithms, similar to the early latent semantic indexing and the later latent Dirichlet distribution. The mode doesn't really matter, especially for what we're trying to achieve.
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The most important thing is to understand how search engines are connected. For example, Google and Bing can understand the word "Super Mario" well and will not associate it with other aspects. They will associate "Super Mario" with "video games" instead of "cat food". If we happen to find that the title of the search results page contains "Super Mario", but most of the content is related to cat food. So even if many internal links in these web pages are connected to the anchor text containing "Super Mario", or have high rankings and high weights, we will not rank these web pages.
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Therefore, search engines such as Google have become more and more intelligent in their understanding of semantic connections, which is similar toGoogle's Hummingbird Algorithmrelated. Hummingbird is an algorithm introduced last fall that changes how search engines understand words and phrases.
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So if you want to know how search engines understand our intent, you have to understand Google and Bing's understanding of the connectedness between words, phrases and topics. This question will touch on many aspects, and it may also come from co-occurring web documents.
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Key wordsthe distance between. I mean, if a lot of webpages have the words "Super Mario" and "Mario", how did Google find "Super Mario" from the word "Mario"? What does the meaning of "Super Mario" have to do with the meaning of "Mario"? Maybe "Super Mario" will appear in many "cat food", but the meaning of "Super Mario" and "cat food" are far from each other. But when it comes to "Super Mario", many pages will appear in the search results, and the search engine may pay attention to the mutual references and links between documents, and will also associate these pages with "Mario", "Luigi", "Nintendo", etc. get in touch.
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Search engines will understand the connection between the anchor text of these links, and also understand the co-occurrence of these words by coordinating the corpus and the bias of the main domain name. Therefore, search engines only pay attention to the updated content on those websites, blogs, news websites, or high-authority domain names, rather than paying attention to the entire content of these websites. Therefore, search engines may understand it in different ways.
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Search engines analyze the questions asked by users, which is an ability that humans do not have. The search engine analyzes the behavior of those who search for "Super Mario" using terms such as "Mario", "Luigi" and "Nintendo".
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Search engines will also use data from Google Chrome, Android, and Google search engines to analyze user clicks and pages visited, and use these data as coordination resources for linking phrases and phrases.
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Search engines may also obtain relevant data from other sources, and use these data to build a very large database of associated words and phrases. For SEO workers, this database seems unimportant because it is unknown.
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If "Super Mario" is used as a keyword, then those lexical phrases that are semantically related to "Super Mario" can be used. If you know which words and phrases a search engine will associate with "Super Mario," you can use those words and phrases. These words and phrases can be written into the webpage to let the search engine know that the content of your webpage is related to "Super Mario", because the webpage contains "Mario", "Luigi", "Princess Peach", "Kuba" and so on. King", "Nintendo", etc., not "cat food", "dog food", "T-shirt", "glass", etc.
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A website gets a link, usually because the anchor text of that link contains words and phrases related to the topic of the website. The anchor text of the link potentially points to your website, so that the website construction can be considered from the perspective of naming conventions and branding. So, when considering product names and product descriptions, you can improve search volume by codifying these terms into formal names and descriptions.
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For the relevant introduction pages on the website, most of them have to consider the official introduction content of the individual or company, including the vocabulary to be used, so the introduction must be edited according to the vocabulary provided by the website, books or meeting content. must be relevant. So when people search for the word "Super Mario," search engines tend to point to the "Nintendo" website.
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Of course, you can also consider using other keywords. These can help when you optimize your pages andlink building, as part of keyword research.
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Now there are various tools to complete these steps, so I won't go into details here.
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There are many downloadable tools and databases online. Code.google.com is an example of a topic modeling tool that is commonly used by the Google search engine.
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Search the web for topic modeling tools, but most modeling tools require a background in website development. Many tools rely on Python databases or APIs, and most also require a corpus. You can download the Wikipedia database as a corpus, or use the top ten Google search engine results as a corpus.
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The whole process will be very difficult, which is why I am keen to try. We explain in detail here, hoping to help you get familiar with these tools as soon as possible, so that you can usewebsite optimizationand keyword research.
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Now you can complete these steps independently. You can go to the website and look at those search results, and carefully study the keywords and phrases used by the top ten websites in Google search. Then think carefully about whether these keywords and phrases are relevant, and whether these keywords and phrases are included in the anchor text? Do people use these keywords and phrases when searching? Are they locally related? Think about it, and learn to take advantage of it. In this way, when doing SEO, you can use these tools proficiently.