{"id":776,"date":"2018-11-28T09:40:04","date_gmt":"2018-11-28T09:40:04","guid":{"rendered":"https:\/\/www.rankmovers.com\/?p=776"},"modified":"2024-02-23T09:28:39","modified_gmt":"2024-02-23T09:28:39","slug":"7-tips-for-optimizing-your-content-for-natural-language-processing","status":"publish","type":"post","link":"https:\/\/www.rankmovers.com\/7-tips-for-optimizing-your-content-for-natural-language-processing\/","title":{"rendered":"How to Optimize Your SEO Content for Google\u2019s Natural Language Processing API"},"content":{"rendered":"

We\u2019ve heard time and time again that Google has increasingly moved away from keyword-based search algorithms. Instead, algorithms have focused more on trying to produce results that adequately answers a person\u2019s question. The main instrument in this mission has always been the search engine\u2019s natural language processing system.<\/p>\n

Below we detail everything SEO professionals need to know about optimizing your content for Natural Language Processing systems.<\/p>\n

\"samsung<\/p>\n

What is Natural Language Processing?<\/h2>\n

Natural language processing (NLP) refers to how computer understand, interact with and respond to natural language. The term natural language itself is a psychological term used to refer to any language used by humans to communicate with each other \u2013 this distinguishes it from coding.<\/p>\n

Why is Natural Language Processing Important?<\/h2>\n

Natural language processing is a huge part of the computer science\/artificial intelligence field. Closer to home, it\u2019s a fundamental part of a search engine. When we interact with Google (or any search engine for that matter), we use natural language to type (or even verbally state) our query, regardless of whether you are using keywords or full sentences. The search engine\u2019s natural language processing functions is what allows it to respond to queries accurately. (Read on below to find a relevant natural language search examples.)<\/p>\n

A Quick History of Natural Language Processing & Search Engines<\/h2>\n

During the 90s, the internet became more accessible to people around the world, and several search engines came into prominence, such as AskJeeves and MSN Search, among others. Many of these early search engines used keyword-based algorithms to determine page rankings. This is why keyword stuffing<\/a> became so popular with early copywriters.<\/p>\n

When Google launched in 1998, they set themselves apart from the pack by using a new algorithm called PageRank to determine rankings. The algorithm used the number of backlinks to determine ranks and not solely keywords. Human-generated links to a specific page became a vital part of determining a page\u2019s importance.<\/p>\n

\"google<\/p>\n

In the years since, various adaptations have been made to Google\u2019s algorithm turning it more into an NLP-based search engine. (It is actually estimated that there are over 250 indicators of quality content in the algorithm.) In 2013, Google introduced the Hummingbird algorithm which made significant changes to the search engine\u2019s natural language processing feature. No longer did writers and internet users have to be as strict with keyword inclusion as they once were.<\/p>\n

In the last five years, even more changes have been made to this system to make it better understand search queries and be less reliant on keywords. In April 2018, Google even released a tool called \u201cTalk to Books\u201d that allowed people to search queries in a cordoned off part of the search engine, and brought up relevant answers that did not have any relevant keywords in them.<\/p>\n

Why is Natural Language Processing Important in SEO?<\/h2>\n

Well, as already previously stated, search engines respond to a user\u2019s query based on what it understands the question to be. As many search engines have moved far beyond the idea of keyword matching, keyword stuffing is no longer a requirement for ranking well.<\/p>\n

Instead, webmasters\/copywriters should now be focusing on creating quality that answers questions in the best way possible.<\/p>\n

7 Tips for Optimizing Your Content for Natural Language Processing<\/h2>\n
    \n
  1. Focus on Topics<\/strong> \u2013 research suggests that topics are more important than keywords. While it is helpful to know how people are asking questions semantically, it doesn\u2019t matter how it\u2019s being asked if no one is searching it.<\/li>\n
  2. Write with the reader in mind<\/strong> \u2013 don\u2019t write posts or pages with the idea that something needs to be uploaded. (This also includes avoiding making your content difficult to read.) Write blogs<\/a> that readers would find helpful in finding out what they want to know.<\/li>\n
  3. Be direct in your answers<\/strong> \u2013Google\u2019s algorithm prefers it when you answer questions directly, i.e. [entity] is [answer]. The longer it takes Google to recognise an answer, the less likely it is to rank you well for a question.<\/li>\n
  4. Keyword salience<\/strong> \u2013 in your keyword research, you need to make sure that you\u2019ve got a focus keyword and you are using clear synonyms but that\u2019s not enough. There are certain words related to the concept that appear on other pages that you will need to include on your page in order for Google to recognise the overall topic you\u2019re going for. (TF-IDF research may help you here).\"example<\/li>\n
  5. Semantic distance<\/strong> \u2013 some keywords may not really work in natural speech, but if you put them in the same sentence (or at least the very same paragraph) Google should still get what you\u2019re trying to say.\"example<\/li>\n
  6. Make use of structured data<\/strong> \u2013 your content needs easy to understand. Structured data<\/a> makes it easier for search engines to understand the purpose of a page. Therefore, it’s more likely to rank.\"dark<\/li>\n
  7. Effective In-Links<\/strong> \u2013 include links that may help the reader and search crawler understand what the concept is about. For example, in a news article about Russia, including in-links on the words \u201cRussia\u201d and \u201cVladimir Putin\u201d.<\/li>\n<\/ol>\n

    NLP and SEO Conclusion<\/h2>\n

    Google\u2019s natural language processing system is a huge factor to take into account when structuring your content. With the algorithm\u2019s strong focus on quality, rather than keyword quantity, there is a definite way every webmaster should be structuring their content.<\/p>\n

    TL:DR? Download our short presentation:\u00a07 Tips for Optimizing Your Content for Natural Language Processing<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

    We\u2019ve heard time and time again that Google has increasingly moved away from keyword-based search algorithms. Instead, algorithms have focused more on trying to produce results that adequately answers a person\u2019s question. The main instrument in this mission has always been the search engine\u2019s natural language processing system. Below we detail everything SEO professionals need […]<\/p>\n","protected":false},"author":15,"featured_media":781,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[89,55],"tags":[],"yoast_head":"\nHow to Optimize Your SEO Content for Natural Language Processing<\/title>\n<meta name=\"description\" content=\"Learn how to optimize your content for the Google algorithm\u2019s Natural Language Processing system. 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