Just to let you know, if you buy something featured here, Mashable might earn an affiliate commission. In today's digitally driven world, it's no longer a surprise to any business that in order to remain viable and competitive, it's essential to have a strong online presence. When it comes down to search, Google is king: there are more than 2.3 million Google searches per minute -- that's absolutely massive. SEE ALSO: Learn how to triple your blog's traffic by taking an online course Your SEO (Search Engine Optimization) strategy is key to not only landing on the first page of Google search -- usually the starting and stopping ground for most users when they query -- it's also essential when it comes down to increasing your overall traffic. For example, if you have an eco-friendly dry cleaning business you're building downtown, you want that to pop up first when locals search for "green dry cleaning service."
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Much like commercials on TV, users are bombarded with content at every turn as they surf. It's overwhelming and as such, marketers are struggling to find ways to capture their attention and stand out. As marketers, not only do we need to conduct extensive research so we can make great content, we also need our content and web pages to be promoted, discovered and engaged with. To help with all facets of content development, user engagement, or "user signals," should be actively tracked in Google Analytics as part of your content marketing campaign. This is important since it's long been speculated that user experience is a ranking factor.
Google's rollout of artificial intelligence has many in the search engine optimization (SEO) industry dumbfounded. Optimization tactics that have worked for years are quickly becoming obsolete or changing. And is it possible to find a predictable optimization equation like in the old days? That is to say, when changes came, they came wholesale. Large and abrupt movements, sometimes tectonic, were commonplace in the past.
Example- List of URLS listed for a search query in search engine Experiments are conducted using real web services datasets and the outcome of the experiments using machine learning confirms an improvement over existing methods in Page Ranking. Supervised Learning algorithms are, K-Nearest Neighbour Ranking Static Ranking 8. KNN RANKING Many supervised learning problems are "classification" problems. KNN is one type of many different classification algorithms. The sheer number of both good and bad pages on the Web has led to an increasing reliance on search engines for the discovery of useful information. Users rely on search engines not only to return pages related to their search query, but also to separate the good from the bad, and order results so that the best pages are suggested first.