AI Gives Intelligent Search a Boost

It never fails. You’re searching for a particular nuance of a common term, or for something where there are multiple meanings, and you find yourself drowning in irrelevant search results.

But science is coming to the rescue. Researchers are finding that by using artificial intelligence, search can learn about context, so that it has an idea about when you mean “surf” for surfing the Web vs. surfing the waves.

You can thank technologies like the semantic web.  In fact, for this reason, some people call intelligent search “semantic search,” because it incorporates this context, writes Sergio Redondo in Search Engine Journal. “Intent, which comes from the user, explicitly states what he or she is looking for,” he explains. “And context could be understood as everything that surrounds a search and makes this go in either direction, i.e., what gives it meaning. Thus, by understanding and connecting intention and context, search engines are able to understand the different queries, both what motivates and what is expected of them.”

Making search more efficient matters because business people spend an awful lot of their time searching for things, according to IDC’s report, Unlocking the Hidden Value of Information. More than a third of information workers’ time is spent looking for and consolidating information from a variety of systems. And with all that, they only find the information they need slightly more than half of the time. That can add up. For an organization that employs 1,000 people, that’s $5.7 million annually spent on unsuccessful searches.

Companies such as Google have been developing intelligent search for some time. Google’s Knowledge Graph, available since 2012, uses sources like Wikipedia and other research sites to provide some quick answers about the search item in hopes of answering your question quicker.

“A search for Taj Mahal immediately brings up a list of facts, photos, and a map of the famous landmark, as well as quick links to other popular uses of the search term (like the musician or the casino in New Jersey),” writes Nathan Ingraham in The Verge. “Google’s goal is to get you to the information you’re looking for in fewer clicks, while also increasing the relevancy of what you see when searching.”

In particular, Google seeks to proactively answer the follow-up questions people typically then search for. For example, the information Knowledge Graph shows when searching for Tom Cruise answers 37 percent of the next search queries made about him, Ingraham writes.

Google is also testing a product called Springboard that is intended to use intelligent search to help users find information across the breadth of Google enterprise products, writes Jon Russell for TechCrunch. “It offers a single search interface which utilizes artificial intelligence to surface information within a user’s suite of Google products,” such as Google Drive, Gmail, Calendar, and Google Docs, he writes.

Similarly, Microsoft’s Delve aggregates information from a variety of sources including email, Yammer, and OneDrive. “Delve displays information that is most relevant for each person based on the work they are doing and the people with whom they are engaging,” wrote Julia White, general manager of Office 365 Technical Product Management, when the product was announced. With Delve, information finds you versus you having to find information.”

Search engines are also using metadata to help answer the question you asked, even if the site doesn’t use the exact phrasing you did, writes Noz Urbina of Urbina Consulting. “Users aren’t looking for a page, they want an answer,” he proclaims.

For example, searching for “Best Band Ever” results in a “carousel” of musician websites, Urbina notes. “Even though many of the pages behind the scenes won’t necessarily actually say ‘best band ever’ on them, these results are listed,” he writes. “This is much more intelligent than mapping keywords straight to pages. The engine is interpreting to get to what I wanted, based on what I said, mapping from an ambiguous concept (‘best band’) to keywords, then to content.”

Intelligent search is being used on companies’ own websites as well, writes Matt Lindner for Internet Retailer. “Intelligent search tools capture customer data in the form of click tracks and browsing behavior to adapt search tools to deliver personalized results,” he writes.

On the other hand, intelligent search in imagery is far from perfect. Even a site as popular as Google Photos has limits in its search capability. “My search for ‘Dog’ turned up several dogs, a fish, two ducks, a group of kangaroos and a baby (note, he wasn’t facing the camera),” Urbina writes. So perhaps intelligent search still has a ways to go.

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