Abstract
Numerous services (email, motion sensor, etc.) emerge and tend to function more comprehensively. What comes with this is the increasing attention to collaboration between them. For example, IFTTT 1 (IF This Then That) enables people to set triggering relationships between various services to be automatically implemented in the cloud. RelRec is an triggering object relationship recommender system, building a bipartite graph representing the relationships between services. We propose an algorithm to rate relationships by similarity, and diversify the results by a modified classic method from graph theory. © Springer-Verlag 2013.
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CITATION STYLE
Dai, Y., Li, G., & Li, R. (2013). RelRec: A graph-based triggering object relationship recommender system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7826 LNCS, pp. 472–475). https://doi.org/10.1007/978-3-642-37450-0_39
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