Recommendations And Discovering Good ReadsPosted by Otis Chandler on March 10, 2011
To tackle this highly complex challenge, Goodreads has acquired a company by the name of Discovereads.com. With their deep algorithmic book recommendation technology, we’re going to be able plumb our database of 100 million book ratings from 4.6 million users to find general patterns of the kinds of books people read and to generate high-quality personalized recommendations.
Book discoverability has become an increasingly difficult problem for readers. More than 300,000 books will be published this year, and the rise of ebooks and self-published books has made the market even larger. It’s a really, really, hard problem to get right, and we we’re excited to have the Discovereads team onboard, because along with being great people, they have a background in machine learning algorithms.
Inspired by the Netflix prize (and with some direct help from a member of second place team), Discovereads’ Brian Percival, left his PhD at Stanford University in Electrical Engineering (in neural circuitry software modeling) to pursue this project. Together with CEO Kyusik Chung, the company has taken three years to refine the technology.
Discovereads combines multiple machine learning algorithms and graph analysis techniques to analyze book ratings and spot trends. Its technology will also improve our unique targeted advertising program. Currently, authors and publishers can purchase ads for their books and target the ads to members who have read similar genres. Hopefully, the new technology will make it more likely that when you see a sponsored book, it will be even more likely it’s something that you’re interested in!
We expect to have Discovereads fully integrated within the next few months. And as always, when it goes live, we will welcome your feedback!
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