LOW ENTROPY BROWSING HISTORY FOR ADS QUASI-PERSONALIZATION
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United States of America
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Dec 8, 2022
app pub date -
Aug 22, 2022
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Aug 22, 2022
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Abstract
The present disclosure provides systems and methods for content quasi-personalization or anonymized content retrieval via aggregated browsing history of a large plurality of devices, such as millions or billions of devices. A sparse matrix may be constructed from the aggregated browsing history, and dimensionally reduced, reducing entropy and providing anonymity for individual devices. Relevant content may be selected via quasi-personalized clusters representing similar browsing histories, without exposing individual device details to content providers.
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