US 11,995,128 B2
Low entropy browsing history for content quasi-personalization
Gang Wang, Jersey City, NJ (US); and Marcel M. M. Yung, New York, NY (US)
Assigned to Google LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Nov. 29, 2021, as Appl. No. 17/537,203.
Application 17/537,203 is a continuation of application No. 16/535,912, filed on Aug. 8, 2019, granted, now 11,194,866.
Prior Publication US 2022/0083599 A1, Mar. 17, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 7/02 (2006.01); G06F 16/00 (2019.01); G06F 16/906 (2019.01); G06F 16/951 (2019.01); G06F 16/957 (2019.01); G06F 16/958 (2019.01); G06N 3/08 (2023.01); G06N 7/04 (2006.01)
CPC G06F 16/906 (2019.01) [G06F 16/951 (2019.01); G06F 16/9574 (2019.01); G06F 16/958 (2019.01); G06N 3/08 (2013.01); G06N 7/046 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for anonymized content retrieval, comprising:
encoding, by a browser application of a computing device, a profile based on a browsing history as an n-dimensional vector by generating a string with values representing each of one or more accesses to an address associated with a corresponding position in the string within a predetermined time period;
determining, by the browser application, a first cluster corresponding to a reduced dimension vector obtained from the n-dimensional vector; and
receiving, by the browser application from a content server, an item of content selected according to an identification of the first cluster.