Enriched search results with applied semantics
The challenge of traditional search
The standard search engine used on most websites analyses inputted phrases as a string of data entered into the search box. Then it returns search results that represent pages containing the exact phrases that match the original query. This means that to get the information truly relevant to the intent, a user needs to know the exact phrase to get it typed into the search box. Not knowing the structure of the webpage or the information location – this seems hardly possible. To give an example: a user enters a search query for “safety”, with the intent to find information concerning driving safety systems. When entering this, the user expects search results to present pages containing information on such security systems. However, it is probable that the information the user queries is actually found on sub-pages that do not contain the phrase “safety”. In this case the user doesn’t receive the relevant search results, although the structure of the site itself includes sub-pages with the information regarding security systems such as ABS, emergency brake assistance, ESC, etc.
Searching for information with Semantic Search
Applying the semantic approach, though, provides the capacity to “understand” the intent of the user searching for information on a page. Semantic Search “analyses” the user query and presents relevant results in a clear way. This way, the user looking for “safety” easily locates the relevant sub-page in their search results, due to the attributes of the data on these pages being semantically related to the phrase ‘safety’.
In addition to semantic search, it is possible to additionally equip a search engine in a module that enables assigning search engine results to theme groups. This approach allows to present the user with information viewed in a logical and transparent manner that can be divided by areas.
Another interesting feature of Semantic Search might be a module that allows the system users to promote pages in the search results list and create synonyms for words ontologies – sometimes even seemingly opposite in meaning or irrelevant, but connected by the brand promo activity. For example, such implementation might allow to connect the name of the celebrity with a kind of advertised washing powder. This means that by entering in the search engine window the celebrity name, search results will return pages regarding the given washing powder brand.
The Semantic Search has already been adapted on the Renault-Nissan Alliance websites. The first Search Insight (Renault project name for Semantic Search) implementations took place for Renault Malta and Renault South Africa in April 2017.
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