
doi: 10.1109/cec.2010.39
Personalized services attract high-value customers. Knowing the preferences and habits of an individual customer, it is possible to offer to that customer well customized and adapted services, matching his needs and desires. This is advantageous for the entity offering the service (e.g., a retailer) as well, as it helps in creating additional sales or improve customer retention. The main unsolved problem today is that the profile of each individual customer would be necessary in order to create such services, posing severe risks regarding privacy and data protection. This paper proposes efficient encryption schemes that allow profiling to be outsourced while preserving privacy. The schemes ensure that the customer is always in control of his profile data, at the same time making shopping data across multiple retailers available to third party service providers to be able to provide targeted services.
| 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). | 6 | |
| 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). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
