The series of YouTube videos “If Google Was a Guy” by College Humor paints a world where our search queries are answered by a man behind a desk. The premise is designed to illustrate how we interact with Google Search, and how ridiculous we would look if we asked these questions to an actual human.

The questions asked range from narcissistic to silly to downright disturbing, and as time goes on Mr. Google gets fed up with the ridiculousness of it all. However, for those paying attention, a second theme presents itself that is more interesting than our habits when we think no one is looking. When searching on Google, the users portrayed rely on keywords that they believe will get them to what they are looking for rather than asking the question they originally had. Since the early days of the internet and even enterprise search, we have been trained to coach the search engine to guide us to the answers we are looking for, creating a whole new dialect for interacting with a search.

In years past, this may have been necessary, but as the algorithms have advanced and natural language processing (NLP) has developed, search applications are now able to understand complete queries and return more relevant results. This is a vast improvement, but still not perfect. The problem with Search UIs now is that they still require the user to use deduction and self-discovery to find the correct result to their question.

If I type the query “How do I change a light switch?” into Google, millions of results are returned. Some of the results are useful, some of them are not. I am therefore required to go through several top results, determining which one will walk me through the process effectively. What if I could have a conversation with the search application just like I would with another human, narrowing in on the correct result automatically by contextualizing my query? And what if you could bring these tools to your organization’s intranet search?

Virtual assistants and chatbots are nothing new, but with Micro Focus IDOL’s expansive Answer Server features, users and/or employees can find the information they need quickly, seamlessly, and without the need to know the exact keywords to type using fact extraction.

How does fact extraction change how users search? A new feature to IDOL Answer Server, fact extraction takes the query, finds the most relevant result, and extracts the key facts relating to the initial query. This allows for rapid, precise insights from your data, and combined with virtual assistant allows for a more conversational Q&A process.

Check out more information on Micro Focus IDOL and its latest features.