A class I took this fall covered recommendation on attributed graphs. On of the research papers on the reading list for the topic was very interesting: it extends the matrix factorization algorithm on a bipartite graph (of users and soundtracks, for eg.) to more general graph structures (which could include soundtracks, artists). I think this exploits local connectivity between artists much better than the vanilla matrix factorization algorithm.<p>[1] Yu, X., Ren, X., Sun Y., Gu, Q., Sturt, B., Khandelwal, U., Norick, B., Han, J. (2014) Personalized entity recommendation: A heterogeneous information network approach. in J Proc. 2014 ACM Int. Conf. on Web Search and Data Mining (WSDM’14)