In terms of architectural styles, microservice architecture, event-driven architecture, and service-based architecture are the most preferred architectural approaches for such a system. For the storage of a content aggregation system, replication and partitioning must be used to improve availability, latency, and scalability.
To increase the performance of the proposed system, various caching methods, load balancers, and message queues should be actively used. The presented architecture aims to provide high availability, scalability for high query volumes, and big data performance.
Finally, this paper presents the high-level architecture of a content aggregation system. The study also provides a detailed description of web crawling and fuzzy duplicate detection systems. The research covers the basic principles of content aggregation, like main criteria for data sampling, automation of aggregation processes, content copy strategies, and content aggregation approaches. It discusses such science and technical problems of content aggregation like web crawling, summarization, searching for fuzzy duplicates, methods of increasing, methods to reduce the delay between the publication of new content by the source and the appearance of its copy in the information aggregator, methods to increase the scalability and performance of similar systems. This research focuses on the main issues and approaches to creating content aggregation systems.
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