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Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback. (arXiv:2109.06077v3 [cs.SI] UPDATED)
Aug. 26, 2022, 1:11 a.m. | Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang
cs.LG updates on arXiv.org arxiv.org
We study the online influence maximization (OIM) problem in social networks,
where the learner repeatedly chooses seed nodes to generate cascades, observes
the cascade feedback, and gradually learns the best seeds that generate the
largest cascade in multiple rounds. In the demand of the real world, we work
with node-level feedback instead of the common edge-level feedback in the
literature. The edge-level feedback reveals all edges that pass through
information in a cascade, whereas the node-level feedback only reveals the …
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