Because of the data deluge in scientific publication, finding relevant information is getting harder and harder for researchers and readers.Building an enhanced scientific search engine by taking semantic relations into account poses a great challenge.As a starting point, semantic relations between keywords from scientific articles could be extracted in order to classify articles.
Indeed, by connecting keywords, the context of the article can be extracted.
This paper aims to provide ideas to build such a smart search engine and describes the initial contributions towards achieving such an ambitious goal.
Today, search engine understanding has evolved, and we’ve changed how we optimize for it as a result. Now, you need to understand what those keywords mean, provide rich information that contextualizes those keywords, and firmly understand user intent.
All of these things are vital for SEO in an age of semantic search.
By examining the queries that lead people to your website, you’ll be able to come up with a group of topics ideal for building content around.
What You Can Do Make a list of keywords and separate them by user intent.
Instead of answering “How big is ,” Google would seek to match the specific keywords from the phrase “How big is it” and return webpages with those exact keywords.
Semantic search also allows Google to distinguish between different entities (people, places, and things) and interpret searcher intent based on a variety of factors including: For example, if you search for “diamondback” after performing 15 searches on snakes, Google will assume that you probably want to learn about rattlesnakes as opposed to the bicycle brand or the villain from Luke Cage.
What You Can Do Create content that clearly and concisely answers a common query at the top of the page before delving into more specific details.
Make sure to use structured data to help search engines understand your content and context.