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Search = Recommendations

It is good to see that some artificial distinctions that have served to hamper progress in delivering truly intelligent computer interfaces are increasingly melting away. In particular, recommendations, when broadly defined, can beneficially serve as a unifying concept for a variety of computer capabilities. In The Learning Layer I defined a computer-generated recommendation as:

A recommendation is a suggestion generated by a system that is based at least in part on learning from usage behaviors.

In other words, a recommendation is an adaptive communication from the system to the user.

And I had this to say about search:

By the way, the results generated by modern Internet search engines are in practice almost always adaptive recommendations because they are influenced by behavioral information–at a minimum they use the behavioral information associated with people making links from one web page to another. This capability was the original technical breakthrough applied by Google that enabled their search engine to be so much more effective than that of their early competitors.

This feature of contemporary Internet-based search also provides a hint at the reason that the users of enterprise search whom I have talked with over the years have been so often underwhelmed by the performance of their internal searches compared with corresponding Internet versions. Historically, there has been little to no behavioral information embodied within the stored knowledge base of the enterprise, and so search inside the four walls of the business has been basically relegated to the sophisticated, but non-socially aware, pattern matching of text–similar to the way Internet search was before Google. Without social awareness, search can be a bit of a dud.

That’s why, as I mentioned in the previous blog, the computational engines behind the generation of search results and recommendations are inevitably converging, and we are therefore witnessing a voracious appetite of search engines for an ever larger and richer corpus of  behavioral information to work with—Google’s new “plus one” rating function being the most recent example.

On this same note, I just happened across this brief, recent write-up that struggles with categorizing a start-up, exemplifying the blurring of search and recommendations, and finishing with the point that, “. . . Google is also increasingly acting as a recommender system, rather than just a web search engine.” Indeed—now on to bringing this convergence to the enterprise . . .


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