Via Paul Lamere, I came across this recent Google blogpost on large scale graph computing. I started reading, and quickly became excited by what I was hearing:
A relatively simple analysis of a standard map (a graph!) can provide the shortest route between two cities. But progressively more sophisticated analysis could be applied to richer information such as speed limits, expected traffic jams, roadworks and even weather conditions. In addition to the shortest route, measured as sheer distance, you could learn about the most scenic route, or the most fuel-efficient one, or the one which has the most rest areas. All these options, and more, can all be extracted from the graph and made useful — provided you have the right tools and inputs.
“Yes!” I thought. ”Yes! I am finally starting to see a growing acknowledgement from one of the Search Majors that when you have a goal-oriented topic, to get from Point A to Point B, there isn’t just a single, most effective, most efficient route. A user might actually want to choose — explicitly choose via input tools — different pathways through all the potential waypoints. Continue reading…
Recent Comments