US 11,734,371 B2
Multi-sensory content authorship aid
Paul R. Bastide, Ashland, MA (US); Robert E. Loredo, North Miami Beach, FL (US); and Matthew E. Broomhall, Goffstown, NH (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Apr. 29, 2022, as Appl. No. 17/661,339.
Application 17/661,339 is a continuation of application No. 16/453,430, filed on Jun. 26, 2019, granted, now 11,361,043.
Prior Publication US 2022/0253498 A1, Aug. 11, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/9537 (2019.01); G06F 16/9535 (2019.01); G06F 16/9538 (2019.01)
CPC G06F 16/9537 (2019.01) [G06F 16/9535 (2019.01); G06F 16/9538 (2019.01)] 17 Claims
OG exemplary drawing
 
1. A computer system for content authorship aid, the computer program product comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage media, and program instructions stored on at least one of the one or more computer-readable tangible storage media for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:
detecting a pause of a user activity of a user exceeding a threshold amount of time;
based on the detection, querying based on one or more inputs associated with the user; and
based on the querying, presenting a recommendation including at least one piece of additional content from a corpus of additional content via calculating a multi-sensory region based on a monitored travel location and one or more of the five sense including sight, sound, smell, touch and taste and a maximum sense distance value for each sense associated with the user;
selecting at least one piece of additional content from the corpus of additional content based on the calculated multi-sensory region;
generating a data model based on the selected at least one piece of additional content; and
selecting a relevant piece of additional content from the generated data model based on determining a topic associated with the selected relevant piece of additional content matches the topic ascertained from the one or more inputs;
wherein presenting the recommendation includes presenting the selected relevant piece of additional content to the user.