Sirvi Autor "Huseynov, Ramil" järgi

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A Recommender System for Improved Data Findability in Open Government Data Portals
(Tartu Ülikool, 2025) Huseynov, Ramil; Nikiforova, Anastasija, juhendaja; Symeonidis, Dimitrios, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Despite the large amount of data available through OGD (Open Government Data) portals, most of it remains “dark data” which means it is not being used. A significant factor contributing to it can be the usability challenges such poor data findability and discoverability associated with these portals. One of the ways to contribute to the solution of these challenges is a recommendation system that can suggest related datasets. Unlike other domains, the recommendation system in the OGD portals is special as it can’t rely on user profile as most OGD portals don’t require authentication. Moreover, this recommendation method should be adaptable to the diverse structures of these portals. Finally, existing recommendation systems for OGD portals mostly focus on tags/category recommendations not datasets recommendations or fail to capture the semantic meaning of dataset’s metadata when making recommendations. This study focuses on these challenges by proposing a new datasets recommendation method based on dataset’s metadata that can capture its semantic meaning without relying on user’s profile and compatible with wider range of OGD portals. To capture the semantic relations between dataset’s metadata the proposed recommendation system relies on pretrained Word2Vec model. Additionally, the prototype of the proposed recommendation system was implemented for the usability testing and feedback was collected and analyzed.