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BookLamp Analyzes Over 30,000 Data Points To Recommend What To Read

BookLamp Analyzes Over 30,000 Data Points To Recommend What To Read

The public face of the Book Genome Project believes it's what's inside a book that matters.

Emma Hutchings

BookLamp uses algorithms to analyze the text of a book, measuring and storing over 30,000 points of data and building what it calls ‘BookDNA.’ Each book on the site has story, language and character DNA, made up of different elements like settings, actors, dialog and description. Users on the site can enter the name of an author or a book title they like and BookLamp will find books with a similar DNA.

This is a new kind of book recommendation tool, far more technical and scientific than displaying books other people have bought along with the one you’re looking at. It matches the actual style and content of the text to similar books.

BookLamp currently gets the text of the books it analyzes directly from the publishers and has partnered with Random House and Kensington Books, amongst others, to catalogue almost 20,000 books so far. Their goal is to attract more publishers to the project so that their collection continues to grow.

BookLamp

Photo by ckaroli

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