Computer program product, computer implemented method, and system for cognitive item selection with data mining

Patent metadata

Field	Value
Publication number	US-11599935-B2
Application number	US-201916397446-A
Country	US
Kind code	B2
Filing date	Apr 29, 2019
Priority date	Apr 29, 2019
Publication date	Mar 7, 2023
Grant date	Mar 7, 2023

Abstract

Methods, computer program products, and systems are presented. The methods include, for instance: ascertaining a user state of a user based on user state data for a cognitive menu selection service from an eatery by use of an electronic menu system. Selection criteria to request one or more items from menus of the eatery is determined based on the user state. A request including the selection criteria is sent and the one or more items corresponding to the selection criteria is obtained and presented to the user by use of a customized virtual reality interface on a personal device of the user.

First claim

What is claimed is:

1. A computer program product comprising:
a computer readable storage medium readable by one or more processor and storing instructions for execution by the one or more processor for performing a method comprising:
ascertaining a user state of a user based on user state data gathered from a personal device of the user, by running the user state data through a selection forecasting model by use of machine learning as being trained with previous user state data and corresponding user states, wherein the user is being provided with a cognitive menu selection service for an eatery by use of an electronic menu system;
determining, based on the selection forecasting model, selection criteria for the user on one or more items from menus of the eatery in a request, wherein the selection criteria correspond to the user state from the ascertaining, wherein the selection criteria is determined by the personal device of the user with use of analysis of the user state data, and wherein the request including the selection criteria is sent from the personal device of the user to the electronic menu system, wherein the electronic menu system is remote from the personal device of the user;
obtaining from the electronic menu system, the one or more items from the menus of the eatery, based on sending the request to the electronic menu system, wherein the one or more items correspond to the selection criteria in the request;
presenting the one or more items from the obtaining to the user, by use of a customized virtual reality interface on the personal device of the user, the presenting comprising: playing, by the personal device of the user, a multi-dimensional augmented reality (AR) presentation clip, the presentation clip associated with the one or more item in the electronic menu system from the menus of the eatery, wherein the presentation clip includes ingredients, flavor, and nutritional facts, respectively corresponding to the one or more item, and wherein the presentation clip in the electronic menu system presents a certain holographic presentation of a dish including the one or more item from the menus of the eatery being prepared for the user on a table, with table settings; and

in response to the presentation clip presenting the certain holographic presentation of the dish including the one or more item from the menus of the eatery being prepared for the user on the table, receiving selection data by the user amongst the one or more items from the presenting and sending the selection data to the electronic menu system to place an order from the eatery.

2. The computer program product of claim 1 , further comprising:
training, prior to the ascertaining, the selection forecasting model that associates the user state data with the user state, wherein training data for the selection forecasting model include previous transactions in a transaction history of the user and previous user state data of the user respective to previous transactions, wherein the user state data include inputs from biometric sensors on the personal device of the user and inputs from preconfigured data sources for dietary preferences and restrictions for the user;
generating a user transaction record corresponding to the order with the eatery based on the selection data by use of a blockchain system, wherein the user transaction record includes the user state data, the selection data, and the order;
updating the transaction history of the user with the user transaction record; and
iterating the training of the selection forecasting model with the user transaction record from the updating, the user state data, and the selection data, to thereby train the selection criteria for future instances of the cognitive menu selection service.

3. The computer program product of claim 1 , wherein the user state includes a level of a physiological need for particular nutrients and a stress level, and wherein the selection criteria include any preconfigured dietary restrictions.

4. The computer program product of claim 1 , wherein the user state includes a level of a physiological need for particular nutrients.

5. The computer program product of claim 1 , wherein the user state includes a stress level.

6. The computer program product of claim 1 , wherein the selection criteria include any preconfigured dietary restrictions.

7. A computer implemented method, comprising:
ascertaining a user state of a user based on user state data gathered from a personal device of the user, by miming the user state data through a selection forecasting model by use of machine learning as being trained with previous user state data and corresponding user states, wherein the user is being provided with a cognitive menu selection service for an eatery by use of an electronic menu system;
determining, based on the selection forecasting model, selection criteria for the user on one or more items from menus of the eatery in a request, wherein the selection criteria correspond to the user state from the ascertaining, wherein the selection criteria is determined by the personal device of the user with use of analysis of the user state data, and wherein the request including the selection criteria is sent from the personal device of the user to the electronic menu system, wherein the electronic menu system is remote from the personal device of the user;
obtaining from the electronic menu system, the one or more items from the menus of the eatery, based on sending the request to the electronic menu system, wherein the one or more items correspond to the selection criteria in the request;
presenting the one or more items from the obtaining to the user, by use of a customized virtual reality interface on the personal device of the user, the presenting comprising:
playing, by the personal device of the user, a multi-dimensional augmented reality (AR) presentation clip, the presentation clip associated with the one or more item in the electronic menu system from the menus of the eatery, wherein the presentation clip includes ingredients, flavor, and nutritional facts, respectively corresponding to the one or more item, and wherein the presentation clip in the electronic menu system presents a certain holographic presentation of a dish including the one or more item from the menus of the eatery being prepared for the user on a table, with table settings; and
in response to the presentation clip presenting the certain holographic presentation of the dish including the one or more item from the menus of the eatery being prepared for the user on the table, receiving selection data by the user amongst the one or more items from the presenting and sending the selection data to the electronic menu system to place an order from the eatery.

8. The computer implemented method of claim 7 , wherein the user state includes a level of a physiological need for particular nutrients.

9. The computer implemented method of claim 7 , wherein the user state includes a stress level.

10. The computer implemented method of claim 7 , wherein the selection criteria include any preconfigured dietary restrictions.

11. The computer implemented method of claim 7 , further comprising:
training, prior to the ascertaining, the selection forecasting model that associates the user state data with the user state, wherein training data for the selection forecasting model include previous transactions in a transaction history of the user and previous user state data of the user respective to previous transactions, wherein the user state data include inputs from biometric sensors on the personal device of the user and inputs from preconfigured data sources for dietary preferences and restrictio

Assignees

• Kyndryl Inc

Inventors

• Pandey Diwesh
• Baughman Aaron K
• Whitman Todd R
• Perrino John P

Classifications

• H04L63/0407

  wherein the identity of one or more communicating identities is hidden (cryptographic mechanisms or cryptographic arrangements for anonymous credentials or for identity based cryptographic systems H04L9/00) · CPC title

• H04L2209/88

  Medical equipments · CPC title

• G06F3/015

  Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection · CPC title

• G06N20/00

  Machine learning · CPC title

• H04L2209/805

  Lightweight hardware, e.g. radio-frequency identification [RFID] or sensor · CPC title