A Brief History of Intelligent Search

Jan 25, 2017

If we asked you right now, could you count how many times you encounter intelligent search in a day? What about that little magnifying glass icon in search bars? With the amount of time we spend in front of a screen, it’s easy to forget how much faster, easier, and more intelligent the internet and searching has become in the last twenty years.

In honor of the early pioneers who made modern intelligent search possible, and in gratitude for not having to sift through piles of irrelevant results anymore, we present to you a brief history of intelligent search.

It was 1997, and the World Wide Web was commonly accessed through CD-Rom. On January 19, Ariadne published “Intelligent Searching Agents on the Web,” describing the new tools that could be trained to search for specific types of information. These agents could learn a user’s preferences from past searches, and moreover, the searching could be done overnight or during the weekend, so the user could do other things in the meantime. Intelligent searching agents could help solve some of the common challenges associated with using search engines, particularly regarding relevant results and information overload.

The new intelligent tools weren’t without their own challenges, however. 

For example, if you wanted a music/film recommendation system to recommend musicians you might like, you might need to spend a significant amount of time teaching that system about your tastes and preferences in order to see consistently good results. Multi-agent software could be downloaded at that time, to perform multiple searches simultaneously, but they often strained computers, preventing use of other programs.

Over the next several years, search engines became more sophisticated. E-Commerce businesses grew enormously, and required search to navigate products. Smartphones became a ubiquitous part of society. Intelligent search needed to become more intelligent, and it did.

By 2013, intelligent search was used, not to return relevant results, but to return hyper-relevant results with fewer clicks, and related suggestions for a searches that would have returned no results at all. Search tools were now increasingly mobile-friendly to keep up with on-the-go users.

Now, two decades after Ariadne’s description of spiders that learn, much of intelligent site search happens behind the scenes of the search itself. Tools can learn not just from past users’ behavior, but from the current user’s real-time actions. Sites can now predict the products customers will prefer or the content that will pique readers’ interest most. Sites can even guide users to the best experience through customer segmentation based on any number of demographics.

Twenty years is a long time on the Internet, and technology changes and grows with it at an ever-accelerating pace. New technology will always drive new consumer demand, will you be ready?