
Adobe’s Identity Graph allows enterprises to more effectively utilize their data in a digital marketing context. We enable enterprises to stitch together all known and anonymous identities of a user between logical and physical devices. This allows companies to perform marketing and analytics in the context of people rather than signals coming from different devices. As a result, a more holistic view of any given customer can be achieved. The graph is built through a combination of deterministic and probabilistic approaches which are applied to both online and offline data. The efficacy of our approach is validated against a real big data set, which has both online data traffic and offline data logs covering more than 1.9 billion devices.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
