How Hard is the Local Search Problem? by Matthew Hurst.
The “local search” problem that Matthew is addressing is illustrated with Google’s mapping of local restaurants in Matthew’s neighborhood.
The post starts:
The local search problem has two key components: data curation (creating and maintaining a set of high quality statements about what the world looks like) and relevance (returning those statements in a manner that satisfies a user need. The first part of the problem is a key enabler to success, but how hard is it?
There are many problems which involve bringing together various data sources (which might be automatically or manually created) and synthesizing an improved set of statements intended to denote something about the real world. The way in which we judge the results of such a process is to take the final database, sample it, and test it against what the world looks like.
In the local search space, this might mean testing to see if the phone number in a local listing is indeed that associated with a business of the given name and at the given location.
But do we quantify this challenge? We might perform the above evaluation and find out that 98% of the phone numbers are correctly associated. Is that good? Expected? Poor?
After following Matthew through his discussion of the various factors in “local search,” what are your thoughts on Google’s success with “local search?”
Could you do better?
How? Be specific, a worked example would be even more convincing.