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Home » Goodnews Stories Srilankan Expats » Articles » Semantic Search: How semantics control search engine searches By Aditya Abeysinghe
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Semantic Search: How semantics control search engine searches By Aditya Abeysinghe

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Last updated: November 13, 2021 3:53 am
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Semantic Search: How semantics control search engine searches

By Aditya Abeysinghe

Search engines are now a part of every internet user’s flow of activities. Users search data using queries and the output is categorized into several categories like websites, videos, news etc. Most search queries typically do not provide information on which data to be shown back. Therefore, a search of related data is often required to show relevant data to the user. Search of relevant data for a query is done by matching semantics to words on a user query.

History of search

Searching on keywords of a query entered by a user was the first method that was used by search engines. In this method, whenever a user submits a query, the entire query was used as the search engine’s input to search for content. Caveats of this technique were the low-quality content displayed as the content with the same name are queried internally and the ability to change the content of websites and other media to match search engine’s content results so that websites are ranked.

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Semantic Search: How semantics control search engine searches By Aditya Abeysinghe

 

Many search engines changed the above method of search to extract semantics from the user queried search and then search the internal systems using these related words to display content. For example, when a user searches for “Best foods to eat to lose your weight”, top search results may include content that contain the same name as well as names such as “Best foods for belly fat”, “Tips to lose weight” etc. Thus, semantic search allows users to find related content by semantically querying for words that are related to words queried by them. Therefore, high-quality content that not only is similar to what the user queried but also content that the user can query for related content are shown. Semantic search methods also make existing content of websites to adapt to frequently updated searching mechanisms to rank them.

New methods to display content

A new display feature which uses semantic searches is knowledge graphs. For example, Google uses its Knowledge Graph to display content as a small infobox next to search results. A simple search of WhatsApp on Google displays a knowledge graph of images, a small Wiki paragraph, and the stable release of WhatsApp, and similar apps. Data sources such as Wikipedia, Google’s indexing databases and several multimedia are queried to display data in one information box to the user.

Rich search results are another method used to display content below certain searched content. Rich results, also called rich snippets, display content in addition to the title, description, and other basic search output of a search engine. For example, a search on a hotel might show its star level, customer feedback and its fee for a single day booking. A rich result for a song might display its artist, length, and year. Rich results for webpages are known to increase the click rate of a webpage as several information about the page is displayed to the user in the results itself.

Google and other popular search engines also use another method called featured snippets to display searched results using data in some websites. Featured snippets are shown at the top of search results and the main use is to show content which answers a user query in the quickest approach. Only websites that have been designed for search engines to obtain information to create rich results and featured snippets are shown when searched.

New methods to search

Semantic search also enhanced new methods to search content such as voice search and image search. Voice Search by Google is one method to search content by voice. Image search allows search that are similar to a user image uploaded. Both these methods provide efficient searching for users when text search doesn’t provide necessary results, and when users need to search when doing tasks where texting is not possible.

Image courtesy: https://quantamixsolutions.com/

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