Literacka creates an intelligent recommendation system dedicated to online bookstores and libraries. The innovative character of planned solution results from automatic analysis of the content of books and the creation of content-based recommendation based on user’s preferences and interests. The designed system is going to be based on artificial intelligence, deep learning techniques and natural language processing. Present e-commerce trends emphasize the importance of a personalized communication, offering a service tailored to the needs of the individual customer and effective gathering of customer data. While the popularity of e-shopping is growing there is a big need to implement newest technological solutions in order to increase the quality of the service and optimize conversion. The system developed by Literacka will generate much more precise and reliable results in a shorter time than the commonly known recommendation systems. It is going to provide personalized service by producing high quality recommendation to users with unique, individual tastes. It will reduce costs associated with making a choice during online shopping experience and can be implemented in many different domain of e-commerce business.
In 2017, Literacka has created a prototype version of the advanced book recommendation system (SHREK) operating on the expert database of books containing over 3 000 items.
Simpact has invested PLN 1 M which will be spent on further research and development of the system as well as sales activities.
The book market is an important element not only of the cultural but also of the economy. The book is a product of the culture industry and as a medium, it has a long-term impact as it shapes view and attitudes of the citizens. Readership affects cultural, scientific and technical development of the society and the economy. For years, the readership level in Poland hasn’t been higher than 37%. The mission of Literacka is to have a positive impact on the readership level by facilitating the selection of book relevant to user’s preferences as well as increasing interest in valuable books that do not have big marketing budgets. Unlike traditional recommendation systems, the system designed by Literacka is not going to be based on the popularity of a given book but on its content and its compatibility with user’s expectations.