Expectations of search are changing rapidly. Until recently, users have generally understood the limitations of search software and were comfortable turning their questions into ‘Key Words’ to help these engines bring back the best results.
Unfortunately, by translating questions into key words, we lose much of the context of a query that might help a truly intelligent system understand what the person is looking for. The question and the context are often lost in the translation.
But this is changing. Over the last few years public search engines like Google, Bing and Yext have rapidly added technologies to their search stack to better identify user intent based on all the words typed as well as other information about the user gleaned from their characteristics and historical behavior.
In the process, the user experience on these public search engines has significantly improved. As a result, users now expect search engines embedded in websites and enterprise applications to behave the same way, understanding their language and providing highly accurate and contextualized answers rather than simply a result list for them to comb through.
The professionals at PureInsights help customers take the next step and add these sophisticated capabilities to their enterprise search applications. We do this by following the path that has already been set by the public search solutions above.
By adding a Knowledge Graph and a Natural Language Processing layer to the existing search stack, most search applications can be enhanced to add Answer Cards and Knowledge Cards to the search experience. At the same time, by fully processing, analyzing and enhancing the content as it is indexed, we can access and present the more granular answers users are seeking. This shortens the time to finding facts of importance and saves users’ time wading through pages of results sets to find critical information. Below are few examples of Google and Bing doing their thing: