Publication: Development of an AI Recommender System to Recommend Concerts Based on Microservice Architecture Using Collaborative and Content-Based Filtering Methods
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2021
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© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Recommender system is a complex software system primarily intended to select the most relevant content based on user’s personal preferences. In order to achieve the set goal, a number of tasks must be completed, including: track user actions across various devices; get product data from a number of sources and maintaining their currency; consolidate the data; create user and product profiles bases on big data in a real-time mode; select recommendations in cold start and highly sparse data environment; assess the quality of the recommender system. Completion of each specific task must not extend the time to complete other tasks. Users must instantly get the relevant content even if the system is heavily loaded, for example, due to a popular event announcement. A workaround may be to divide the system into independent components with the ability to scale specific services. Microservice architecture examined in this article intends to ensure required flexibility due to asynchronous message exchange via a data bus and other principles offered by SOA concept. Apart from interaction between the components, the article also introduces the results of development of each specific service from asynchronous user action tracker to recommender engine based on the hybrid approach that includes collaborative and content-based filtering methods, and the knowledge-based approach using Artificial Intelligence techniques. Special attention is paid to a subject category with a number of aspects that prevent applying generic approaches to building recommender systems.
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Malynov, A. Development of an AI Recommender System to Recommend Concerts Based on Microservice Architecture Using Collaborative and Content-Based Filtering Methods / Malynov, A., Prokhorov, I. // Advances in Intelligent Systems and Computing. - 2021. - 1310. - P. 241-252. - 10.1007/978-3-030-65596-9_31