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AssigneesAT&T Intellectual Property I, L.P., Board of Regents, The University of Texas System
InventorsKadangode K. Ramakrishnan, Divesh Srivastava, Tae Won Cho, Yin Zhang
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Recommendation systems are widely used in Internet applications. In current recommendation systems, users only play a passive role and have limited control over the recommendation generation process. As a result, there is often considerable mismatch between the recommendations made by these systems and the actual user interests, which are fine-grained and constantly evolving. With a user-powered distributed recommendation architecture, individual users can flexibly define fine-grained communities of interest in a declarative fashion and obtain recommendations accurately tailored to their interests by aggregating opinions of users in such communities. By combining a progressive sampling technique with data perturbation methods, the recommendation system is both scalable and privacy-preserving.
A method for generating a recommendation, the method comprising:
An apparatus for generating a recommendation, the apparatus comprising:
A non-transitory computer readable medium storing computer program instructions for generating a recommendation, which, when executed on a processor, cause the processor to perform a method comprising:
Dependencies are inferred from the claim text.