By Dr. Eric Glover, Searchme’s Classification Architect. Eric is responsible for the design and implementation of Searchme’s categories feature, a seemingly simple tool that springs from an exciting area of artificial intelligence (AI) research and development.

Search companies aren’t clueless about the fact that users have different needs. To deal with an ambiguous query, most will use some type of “mixing”.

With “Saturn”, for example, they will present results from both the car company and the planet. Some even go a step further and offer “related searches”, which help a user by presenting queries that others might have asked, such as “Saturn cars” or “Saturn Vue”.

Unfortunately, commercial search engines don’t do “mixing” based on knowledge about the explicit meanings of a query or of web pages. But what would happen if they did? What would happen if search engines actually “understood” that “Saturn” had multiple meanings, not just because different results were manually “mixed”. What if they knew that www.saturn.com was about “car companies” and that “en.wikipedia.org/wiki/Saturn” was about “astronomy”? Could they use this knowledge to help separate out results by meaning, thus reducing a user’s difficulty in locating what they want?

The ability to “separate out by meaning” brings us to the subject of ontology – which is what we think is required to create the search of the future.

Next – Part Four: How Ontology Gives Us Better Search