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It does not store any personal data.Īdvertisement cookies are used to provide visitors with relevant ads and marketing campaigns. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. General purpose platform session cookies that are used to maintain users' state across page requests. The cookie is set by GDPR cookie consent plugin to record user consent for the usage of cookies under the category “Uncategorized.” The purpose of this cookie is to check whether or not the user has given the consent to the usage of cookies under the category 'Performance'. This cookie is set by GDPR Cookie Consent plugin. The purpose of this cookie is to check whether or not the user has given the consent to the usage of cookies under the category 'Necessary'. The purpose of this cookie is to check whether or not the user has given the consent to the usage of cookies under the category 'Analytics'. The purpose of this cookie is to check whether or not the user has given their consent to the usage of cookies under the category 'Advertisement'. These cookies do not store any personal information. This category only includes cookies that ensures basic functionalities and security features of the website. Necessary cookies are absolutely essential for the website to function properly. “We want to help people find books that they will enjoy – and big data is an extremely effective way of doing that.” “Ultimately, machine learning algorithms are a tool,” Braziunas explained. There are personalized lists that live on the homepage, “Next Read” emails sent when a user is close to finishing their current book, related books (“people who read this also enjoyed…”) on each product page and a host of others. These recommendations are then delivered to users via a variety of channels across the platform. Recommendations are delivered via several channels – the homepage, product pages and emails. Unlike other e-commerce sites or bricks-and-mortar bookstores, Kobo looks at more than just purchases when generating recommendations, making use of actual eBook content, metadata (author, series, genre), and other attributes such as popularity, ratings and publication date. “Our goal is to make the entire website personalized, to customize to individual interests, whatever those may be.… To do this we take into account a variety of data points – offering what we hope is a richer, more relevant list of suggested reads,” said Braziunas. Thus, recommendations a customer sees may be very different from one day to the next (in some cases, even hour to hour). So-called “machine learning,” the science of programming computers to learn by themselves, allows Braziunas and his team to offer recommendations to readers based on the most relevant real-time data. Personalized recommendations take into account multiple data points – not just recent purchases. A user might be interested in both science fiction and biographies, but if the last few books she has read are science fiction, the recommendation system will assign a higher value to that topic, leading the user to receive more sci-fi recommendations than biography. Kobo analyzes the titles in a user’s library, and automatically extracts the main topics of interest – using unsupervised machine learning techniques – and creates a weighting of these interests based on their relative importance to the user. “If you see a bookshelf and recognize some of the authors and books on it, it is likely you will enjoy reading the other books as well.”
“Modern recommendation systems, no matter how technically sophisticated, are based on a very simple foundational idea: similar people like similar things,” explains Kobo’s Director of Big Data, Darius Braziunas. With a catalog of more than 5 million books and millions of readers around the globe, Kobo is able to take voluminous amounts of data and process it into helpful recommendations.
To help make discovery easier, Rakuten Kobo is harnessing the power of big data on their eReading platform. With limited time and infinite choice, readers regularly cite the difficulty of selecting the “right” book as a barrier to reading more. Choosing your next read can be an agonizing process.
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