I’m still near the starting point in my travels through recommendation services and their underlying algorithms. It’s always a great help therefore to meet a more experienced knowledge hiker returning from the other direction who can offer a better sense of the terrain ahead.
We received a comment from Sachin Kamdar, founder of recommendation startup Parse.ly, in response to a post last week on Freebase and knowledge networks that gave us just such an insight.
Kamdar’s point is that you can get pretty far—but not all the way, of course—by extracting patterns from datasets. Even a simple pattern matching algorithm can be useful.
Parse.ly, by the way, employs both data mining techniques and language processing in generating its recommendations.
So how far can you go with pattern matching and a little semantic analysis?
To find out we tried Google Sets.Continue reading