Abstract
This chapter provides more details on advanced research work proposed in LBSNs, and deepens in the algorithmic side of each method. We present algorithms for generic and personalized recommendations. For readability reasons, we have categorized the state-of-the-art methods in different algorithmic families such as matrix and tensor factorization, graph-based methods, and hybrid models.
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Symeonidis, P., Ntempos, D., Manolopoulos, Y. (2014). Algorithms. In: Recommender Systems for Location-based Social Networks. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0286-6_6
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DOI: https://doi.org/10.1007/978-1-4939-0286-6_6
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