Abstract
Datasets are an integral part of contemporary research on recommender systems. However, few datasets are available for conventional recommender systems and even very limited datasets are available when it comes to contextualized (time and location-dependent) News Recommender Systems. In this paper, we introduce an educational news dataset for recommender systems. This dataset is the refined version of the earlier published Adressa dataset and intends to support the university students in the educational purpose. We discuss the structure and purpose of the refined dataset in this paper.
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Xing, Y., Mohallick, I., Gulla, J. A., Özgöbek, Ö., & Zhang, L. (2020). An Educational News Dataset for Recommender Systems. In Communications in Computer and Information Science (Vol. 1323, pp. 562–570). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-65965-3_39
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