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Recommender System Library

Student: Novichkova Anastasia

Supervisor: Stanislav N. Fedotov

Faculty: Faculty of Computer Science

Educational Programme: Software Engineering (Bachelor)

Final Grade: 9

Year of Graduation: 2021

Recommender systems are an important part of our everyday life. They help customers to find what they need and speed up the purchase process increasing customers’ loyalty and improving retention. Not every business can afford developing a recommender system of its own, so open-source and even commercial market-ready solutions are of great value. The vital features of commercially usable libraries are convenient integration into projects, convenient development interface, and a sufficient set of implemented algorithms. This paper reviews existing solutions and describes a new library that can simplify interaction with recommender systems. This paper reviews existing solutions and describes a new library that can further simplify interaction with recommendation systems. The purpose of the work is to develop offline and online versions of the library for working with recommendation systems.

Full text (added May 21, 2021)

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