Graph-Based Recommendation for Sparse and Heterogeneous User Interactions
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Recommender system research has oftentimes focused on approaches that operate on large-scale datasets containing millions of user interactions. However, many small businesses struggle to apply state-of-the-art models due to their very limited availability of data. We propose a graph-based recommender model which utilizes heterogeneous interactions between users and content of different types and is able to operate well on small-scale datasets. A genetic algorithm is used to find optimal weights that represent the strength of the relationship between users and content. Experiments on two real-world datasets (which we make available to the research community) show promising results (up to 7 % improvement), in comparison with other state-of-the-art methods for low-data environments. These improvements are statistically significant and consistent across different data samples.
|Titel||Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings|
|Redaktører||Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Annalina Caputo, Udo Kruschwitz|
|Status||Udgivet - 2023|
|Begivenhed||45th European Conference on Information Retrieval, ECIR 2023 - Dublin, Irland|
Varighed: 2 apr. 2023 → 6 apr. 2023
|Konference||45th European Conference on Information Retrieval, ECIR 2023|
|Periode||02/04/2023 → 06/04/2023|
|Navn||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
Acknowledgements. This paper was partially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 893667 and the Industriens Fond, AI Denmark project.
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.