Friday, January 9th, 2009

Will you like it?

I added something I’ve been working off-and-on for about a year*: “Will you like it?” Here’s an example, correctly predicting that I will like Nabokov’s King, Queen, Knave:

You’ll find the section on work pages.

Because it requires a lot of processing, you have to click to get the result. Here it is, correctly predicting that I would not enjoy a popular book about Knitting:

Each assessment has a “certainty” score (eg., “high,” “low,” etc.) based largely on how popular the book is. You can see the raw scores by hovering over the downward arrow.

How good is it? Meh. It’sokay.

This is a devilishly hard algorithm to get right. I have some ideas for improvement, but it’s fundamentally a lark and a conversation piece at present, so I don’t want to waste too much time on it.

How it works. In case you’re interested, it works completely apart from our book-to-book recommendation system, or the system that aggregates those recommendations into member-specific lists of 1,000 recommended books. Instead, “Will you like it?” works directly from the data, examining the users who have a book and how their books relate to yours.

As such, it isn’t very good at sussing out where your tastes differ from those of people who share your books. For example, my large collection of books on Greek history match me up with people who enjoy other ancient history, but I am not that interested in early Republican Rome, no matter what the algorithm thinks.

What’s interesting? I’m not going to claim it’s perfect, but it’s interesting that, to my knowledge, nobody’s every tried this before.

I think this is yet another case of Amazon limiting the horizons of what people imagine online, particularly in the online book world. Amazon pioneered book-to-book and user-to-book reviews. The work was groundbreaking but it was also routed in commercial success. User-to-book recommendations drive customers to books they’ll like and book-to-book recommendations help them find the perfect book, as well as increase the number of items in each order. Giving people honest assessments of whether they’ll like a book is murkier. Does Amazon want to tell a customer they won’t enjoy something? And what if they’re wrong?

Meanwhile, LibraryThing succeeds by being fun and interesting, not by selling books. It gives us a rare freedom to invent features that don’t sell books, like our Unsuggester—what books will you hate?—and now this.

I started a topic to discuss it.


*Don’t worry. This didn’t distract. I just pushed two combination/separation bug fixes, and Chris and I are hard at work on the catalog, in preparation for some larger changes (ETA: one week?).

Labels: amazon, new features, recommendations

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