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Recommendation Engines

Some time back I started pondering the challenges of automating affinity in the enterprise – that is determining people you should know based on your digital footprint. Part of my exercise has had me looking into the recommendation engines that others have implemented and seeing what makes them tick.

When I first started to really look at the Amazon recommendation engine, noticed a pattern. The fiction books recommended to me – all seemed to be same authors I've already indicated interest in (either by buying or rating). No new authors were coming up. I thought this was odd – I certainly did not need to be recommended a book from Grisham, Clancy, or Ludlum. In exploring the non-fiction books, the recommendations better – but really seemed too topical. Just because I bought a book on corporate governance a few years ago during my MBA program studies does not mean that I am interested in it now. That situation is easily rectified by telling Amazon to ignore that purchase for recommendations, so I really won't gripe about it.

An interesting thing happened the other day though when I cranked up my Kindle. I started getting recommendations for fiction books from other authors. What was the difference? I purchased The Hitchhiker's Guide to the Galaxy on my Kindle. Apparently, Grisham / Clancy / etc. aren't good connectors or predictors. But buy something from Douglas Adams and whammo!, you get recommendations. So now I've uncovered many authors and books I may be interested in, and am sorely in need of some free time to discover them.

The unfortunate side effect to this discovery is that I no longer have an out based on my initial observations of Amazon. My guess is that when you only buy and rate the highly popular authors, the ranking algorithm becomes skewed toward those large pools and does not uncover the books/authors that may be equally good but less purchased. So, my investigation continues.

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