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Abstract

The invention provides, in some aspects, a statistical algorithm-driven digital system for automated optimization of a large number of key performance indicators (KPI) involved in social digital interactions among the users, contents and advertisement, further augmented by data-driven verification and recommendation. The users include humans from diverse socio-cultural-economic groups, whose identity may be pseudonymous (though persistent), and whose explicit features may remain private, though statistically imputable. The contents include webpages, downloads, videos, music, or other content accessed by the users. The advertisements include product placement, branding, appeal, surveys, or other third-party contents, not explicit sought by the user. A server application executing on the server digital device responds to requests received from the client digital devices for delivering thereto requested digital content. The server application customizes at least a selected piece of digital content it delivers to a respective client application (in response to such a request) based on ordinal rankings for users, contents and advertisements, computed by a tensor based statistical inference algorithm, as described in a preferred embodiment of this invention. The rankings computed are predictive of various aspects of user's future social interactions, as determined by the past statistical data, summarized in sparse high-dimensional tensors.

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First Claim