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Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2021) Variational Bayesian representation learning for grocery recommendation. Information Retrieval, 24(4-5), pp. 347-369. (doi: 10.1007/s10791-021-09397-1)
Mccreadie, R. et al. (2021) Leveraging data-driven infrastructure management to facilitate AIOps for big data applications and operations. In: Curry, E., Auer, S., Berre, A. J., Metzger, A., Perez, M. S. and Zillner, S. (eds.) Technologies and Applications for Big Data Value. Springer: Cham, pp. 135-158. ISBN 9783030783068 (doi: 10.1007/978-3-030-78307-5_7)
Meng, Z. et al. (2020) BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 588-590. ISBN 9781450375832 (doi: 10.1145/3383313.3411524)
Meng, Z. , Mccreadie, R. , Macdonald, C. and Ounis, I. (2020) Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 681-686. ISBN 9781450375832 (doi: 10.1145/3383313.3418479)
Sanz-Cruzado, J. , Castells, P., Macdonald, C. and Ounis, I. (2020) Effective contact recommendation in social networks by adaptation of information retrieval models. Information Processing and Management, 57(5), 102285. (doi: 10.1016/j.ipm.2020.102285)
Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2019) Variational Bayesian Context-aware Representation for Grocery Recommendation. In: 13th ACM Conference on Recommender Systems (RecSys19) - CARS 2019 Workshop, Copenhagen, Denmark, 16-20 Sept 2019,