US 12,381,938 B2
Computer-implemented systems and methods for a user-controllable parameter
Jeffrey D. Brandstetter, San Francisco, CA (US)
Filed by Jeffrey D. Brandstetter, San Francisco, CA (US)
Filed on Feb. 14, 2023, as Appl. No. 18/168,610.
Application 18/168,610 is a continuation of application No. 17/120,399, filed on Dec. 14, 2020, granted, now 11,595,466.
Application 17/120,399 is a continuation of application No. 16/789,636, filed on Feb. 13, 2020, granted, now 10,868,859, issued on Dec. 15, 2020.
Application 16/789,636 is a continuation of application No. 16/399,000, filed on Apr. 30, 2019, granted, now 10,567,488, issued on Feb. 18, 2020.
Application 16/399,000 is a continuation of application No. 14/677,040, filed on Apr. 2, 2015, granted, now 10,284,630, issued on May 7, 2019.
Prior Publication US 2023/0188595 A1, Jun. 15, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 67/10 (2022.01); H04L 67/306 (2022.01)
CPC H04L 67/10 (2013.01) [H04L 67/306 (2013.01)] 22 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
accessing an item pool, wherein the item pool contains data associated with a plurality of literature items;
providing the plurality of literature items to a model that is configured to output a literature item based on parameters of the plurality of literature items in the item pool, characteristics of a current literature item, and a user-controllable parameter;
receiving the user-controllable parameter via a user interface, the user interface being a slide bar for a characteristic that includes a plurality of positions relative to the baseline position associated with the current literature item, the characteristic being based on language of the current literature item, the slide bar being configured for inputting a preference for an increase or decrease of the characteristic relative to the current literature item, wherein the user-controllable parameter indicates a user preference for the characteristic of a next literature item relative to the current literature item;
providing the current literature item and the user-controllable parameter to the model; and
delivering the next literature item identified by the model based on the current literature item and the user-controllable parameter.