From mocoNews:
BookLamp.org is the public face of the Book Genome Project, which was founded by University of Idaho students in 2003 and aims to identify, track, measure, and study the features that make up a book using computational tools. Other book recommendation sites exist, but they tend to rely on user-submitted data and social recommendations. BookLamp is different because it actually analyzes the books’ text. Its algorithm breaks books down into 32,160 elements: “StoryDNA” (“setting” and “actors”), language and character DNA. (Here is some more detailed information on how that works.)
“The analogy I use the most is that if you’ve eaten a chocolate cake and you wanted to find other cake that tasted the same, you’d need to know not just the ingredients, but the percentage and the preparation,” Aaron Stanton, the site’s founder (who originally gained some internet fame for his project Can Google Hear Me), said. “From that perspective, thematic ingredients balance the book, and the writing style is the preparation: How is language prepared to deliver that storyline to the reader?” Each book featured on the site has a “BookDNA” overall profile including all of those elements.
“Since the suggestions are based on what is inside a book alone, it is not influenced by things like marketing budgets or author popularity, which drives social suggestion engines,” Stanton said. “We are an equal friend to the front, mid, and backlist author. Or as we like to say, ‘We’re as likely to find you Richard Bachman as Stephen King.’”
