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A project implemented during my dissertation at the National Technical University of Athens. This project was a part of a bigger research project for a Data as a Service (DaaS) Marketplace architecture that was published on April 2020. The aim of my part in this project was to enhance the core functionalities offered by Elasticsearch towards two directions: both the discovery and the ranking. It was developed to extend the search results, capturing semantic relations between different terms, and on the other hand, to revise the Elasticsearch default scoring algorithm used to rank those results. The recommendation system implemented was then compared to Elasticsearch queries, showing an improvement on the percentage of cases where the proposed system returned a more fitting result than the simple Elasticsearch. The dissertation project was implemented in Java using Spring Boot and Elasticsearch.
