Facebook is now valued at $15 billion by many estimates.
Soon the young company will have to prove it’s really worth it.
That’s no small task.
That maxim has proven true of Google in Web search and Amazon in e-commerce sales and product recommendations.
A Facebook representative declined comment for the story.
Traditional ad networks would kill for all that information in one place.
But with that data comes some interesting machine learning problems, experts say.
Machine learning is a broad term in the field of artificial intelligence.
It refers to developing algorithms that can discover patterns in data and learn from them.
Google, for example, has used probabilisticBayesianmodels to serve results to data searches based on keywords.
With advertising, it’s all about matching the right person to the right ad.
And on an individual level, that’s a tall order.
Many thornyissuescan arise, too, such as trusting what people post about themselves.
On social networks, people are prone to misspellings, random statements, and exaggeration.
In that kind of social environment, ads can be ineffective orannoying.
That’s why Facebook must perfect a subtle product placement or recommendation system.
To do it, it will have to invent algorithmic tricks.
It does this by looking at people’s habits in aggregate, rather than as individuals.
But this requires massive computing power," said Paul Martino, founder of Aggregate Knowledge.
Amazon’s system automatically analyzes your purchase history and looks for the same buying patterns among other shoppers.
Then it can suggest items you might also like.
That way, movie or music studios could “suggest” entertainment in the form of a product placement.
The ad online grid could then target ads for local sushi restaurants to members of that group.
But the company hasn’t deployed this methodology on a wide scale.
Facebook is also a tremendous barometer for public opinion.
The big search sites have done some work in this area.
Yahoo targets ads similarly, but it also sells behaviorally targeted ads to marketers.
CNET News.com’s Elinor Mills contributed to this report.
