Semantic search, unlike traditional search, is based on showcasing information related to the users’ intent rather than just focusing on the keywords used. Semantic search is a technique used in which a query not only aims to find the relevant keywords but actually tries to determine the intent and contextual meaning of that particular query. This provides a more efficient and meaningful array of search results from the various online repositories.
Instead of using the traditional means like Google’s PageRank to predict relevancy, Semantic search is mostly based on the science of meaning in the language to produce relevant data for the user rather than the user having to figure out the required information on their own based on keywords.
KEYWORD SEARCH VS SEMANTIC SEARCH
Companies like Google primarily used to rely on traditional keywords and displayed information from billions of pages with relevant keywords typed in by the user. This resulted in the user being bombarded with hundreds of pages with the ones matching the exact terms being displayed on the first page based on priority. This was directly proportional to the query being searched for and the pages with had the maximum keywords. However, Google search engine is making inroads into the Semantic search domain by implementing certain protocols that enable it to work even better, but it’s is a slow process.
Semantic search works very differently to a keyword search. The difference here is that instead of sharing information that it hopes to have the answer for, Semantic search actually tries to answer the question. Instead of linking a query based on the words used, the Semantic search protocols tries to showcase information based on various data attributes.
For example, if you search for ‘best Android smartwatch,’ a keyword search engine would yield results based on the keywords and the number of times it's mentioned on a web page, hoping that one of them would provide the answer that you are looking for. On the other hand, a semantic search would yield a different result as shown in the example below. Here the search result in mainly based on the intent of the user and gives you not only the most relevant answer, but also displays attributes and other useful information about the product. The interface shown is simplified and elegant, and for the most part, Graphiq Search does it the best.
Ultimately, the aim of search engines is to decipher the data keyed in by the user and to provide the most relevant information. Going forward, semantic search will play a vital role in how search engines work. The idea is to provide the user with the useful information that is based on quality and not a trove of information for the user to scroll through to find the answer they are looking for.