Apple recently purchased BookLamp, which uses analytics to produce reading recommendations, for between $10 million and $15 million, according to TechCrunch. Apple has not stated their plans for BookLamp — nor do they plan to. "Apple buys smaller technology companies from time to time,” a statement released by the computer giant claimed, “and we generally do not discuss our purpose or plans.” It’s likely, though, that Apple will use BookLamp’s technology to improve upon its already existing iBooks service.
Beginning as a University of Idaho project in 2003, BookLamp has often been described as a “Pandora of books,” though founder and CEO Aaron Stanton prefers to think of it as the “Book Genome Project.” The service looks at the so-called “DNA” of a text to find major themes and plots, and matches these to other books to devise reading recommendations.
“Say you’re looking for a novel like the The Da Vinci Code,” Stanton posited in a 2011 interview with Publishing Perspectives. “We have found that it contains 18.6 percent Religion and Religious Institutions, 9.4 percent Police and Murder Investigation, 8.2 percent Art and Art Galleries, and 6.7 percent Secret Societies and Communities, and other elements — we’ll pull out a book with similar elements, provided it is in our database.”
In short, BookLamps claims to tell you whether or not a book is right for you — which is a lot murkier than it sounds. The “recipe” of a book is a delicate balance; how would BookLamp find the essential ingredients of a text that employs, for example, a stream of consciousness narrative, like James Joyce’s Ulysses or Virginia Woolf’s To the Lighthouse.
Admittedly, I have never used BookLamp (and, after the Apple acquisition, it is no longer available), but I imagine it has the same issues as Pandora. (Just because I’m playing the Fleetwood Mac station does not mean I want to listen to Stevie Nicks’s solo albums.) Taste is a precarious thing, and I’m not quite convinced that it can be gauged with an algorithm. I typically don’t enjoy dystopian fiction, but Margaret Atwood’s Oryx and Crake is one of my favorite books — yet even then, I found myself dozing off while reading the sequel and I didn’t bother with the third book. What’s the algorithm for that? What’s the recipe?