"Do you really care about the temperature or humidity or wind velocity? Or do you actually care about catching cold in a windy weather or perhaps getting a heat-stroke in tropical summer?
When you track the Click Through Rates (CTRs) of your email marketing campaigns, do you really bother about the number of people who opened your emails? Or are you looking for the users of the system who are more likely to buy your product?
Which ones among your Facebook Close Friends are the most likely to hang out with you in case you asked them for dinner tonight?
Let's skip the number-crunching analysis that follows. How about building systems which directly take you to the answers you are looking for, without worrying too much about the numbers that play a role in between? This talk opens a perspective of arriving at a solution by applying graph theory in practice. Here we discuss common scenarios where a graph database could fit and scenarios where it need not fit. The talk covers some of the most popular Open Source graph databases available right now.
This talk also covers various Ruby bindings for some Open Source graph databases. Rubyists who are on their course of building software which involves recommendation, predictive analysis, collaborative filtering and context mining, should find this talk useful."