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The Role of Machine Learning in Google Search Algorithms
The search engine optimisation (SEO) industry has been having a lot of debate lately about machine learning and what the process is. Machine learning comprises of three sections; data, maths, intuition.
Google search algorithms use machine learning to provide an improved user experience. A Google engineer will tell the algorithm what features are important, along with rules that the algorithm must follow.
The process involves the engineers providing the machine with human-labelled examples of good and bad results based on different scenarios, helping the machine improve, learn, and grow.
Taking the information provided by the Google engineers, the machine identifies different weights for features provided, ensuring quality results. The Machine Learning Algorithm runs and provides live results. Yet this is only the tip of the iceberg.
The machine learning cycle is a constant process. Google and Bing, both provide their algorithms with ongoing feedback, helping them improve and evolve. This feedback is provided as labelled data that may correct the machine or reinforce it when it works correctly.
Once the wrinkles are ironed out, the machine runs on a three step process:
Machine learning in Google Search Algorithms still require human intervention. Google and Bing both have human raters or judges. These humans are responsible for assessing the results, labelling them as a success or failure.
The success of the machine learning depends on each case scenario or context. Google will not share the exact rules that they determine as a success or failure. The search engines also receive their feedback through search engine results pages (SERPs).
Any labelled data provided to the machine helps it adjust and improve. The aim of machine learning in Google's Search Algorithms is to provide accurate and relevant results to users, improving user experience, which has been the focus of Google for many years. Google wants to improve its users search experience, and machine learning is making this possible.
The machine learning of Google search algorithms is seeing the algorithm as a measuring model. It is responsible for measuring success and failure, then adapting accordingly. Yes, humans do play an important role, the machines are lot able to run free.
These machines learn at an exponential rate, which has resulted in the algorithms becoming more sophisticated.
Machine learning is streamlining Google search algorithms with the help of human intervention. As the machine learns and improves, it produces accurate results for users, improving their experience, while providing quick and direct answers to their queries. Genie Crawl is here to provide a customised digital marketing strategy, ensuring your strategy aligns with the latest Google search algorithms. Get in touch today to find out more.
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