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Enhancing personalization via search activity attribution
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
Online services rely on machine identifiers to tailor services such as personalized search and advertising to individual users. The assumption made is that each identifier comprises the behavior of a single person. However, shared machine usage is common, and in these cases, the activities of multiple users may be generated under a single identifier, creating a potentially noisy signal for applications such as search personalization. We propose enhancing Web search personalization with methods
doi:10.1145/2600428.2609510
dblp:conf/sigir/SinglaWHH14
fatcat:ofhm43dx3fbchnefqvz2cn2kfi