BookLamp is a book recommendation system that uses the full text of a book to match it to other books based on scene-by-scene measurements of elements such as pacing, density, action, dialog, description, perspective, and genre, among others. In other words, is a for books, based on an author’s writing style. If you match against multiple books, the self-learning system adjusts your formulas to make the match specific to your tastes. As the system moves out of beta, it will also incorporate human feedback into the recommendation systems, blending the strengths of social networks with the strengths of computer analysis. Ultimately, we want users to be able to create and share their own formulas, creating a community of book lovers that have tools to discover and share books in a way never before possible.



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