# US 10,373,213 B2 · Rapid cognitive mobile application review

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- Number: US 10,373,213 B2
- Document ID: US10373213B2
- Status: Granted
- Kind: B2
- Application number: 14/879,189
- Filed: 2015-10-09
- Published: 2016-09-08
- Granted: 2019-08-06
- Earliest claimed: 2015-03-04
- Assignees: International Business Machines Corporation
- Applicants: International Business Machines Corporation
- Inventors: Vijay Ekambaram; Ashish K. Mathur; Vivek Sharma
- Web page: https://patentgrep.com/patent/US10373213B2

## CPC

- G06Q 30/0282: Rating or review of business operators or products
- G06F 3/012: {Head tracking input arrangements}
- G06F 3/013: {Eye tracking input arrangements (G06F3/015 takes precedence)}
- G06T 1/0007: {Image acquisition}
- G06V 40/174: {Facial expression recognition}
- G06V 40/179: {metadata assisted face recognition}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

Mobile application reviewing is provided. An interaction, made by a user of a wearable device is identified. One or more facial expression data is received. A screenshot of a mobile application on a mobile device is captured. A user sentiment, corresponding to the screenshot, is determined, wherein the sentiment is based on the facial expression data. A mobile application rating corresponding to the user is determined wherein the mobile application rating is based on one or more screenshot ratings corresponding to the user.

## Claims

### Claim 1

A method for generating in-application user feedback, the method comprising:
issuing, by a first mobile device, an instruction to a second mobile device to capture a screenshot of a mobile application on the second mobile device based, at least in part, on facial expression data of a user of the second mobile device;
determining, by the first mobile device, a sentiment of the user corresponding to the facial expression data based, at least in part, on:
learning characteristic facial expression data associated with the sentiment of the user;
comparing the characteristic facial expression data to the one or more facial expression data; and
adjusting the sentiment, based on the characteristic facial expression data, into an adjusted sentiment;
identify, by the first mobile device, at least a first user interface element and a second user interface element of the first mobile application included in the screenshot, wherein (i) at least one of the first user interface element and the second user interface element is a keyboard feature of the mobile application and (ii) the first user interface element obscures at least a portion of a feature associated with the second user interface element; and
generate, by the first mobile device, a rating for the first user interface element that relates to an accessibility of the feature associated with the second user interface element of the mobile application included in the screenshot based, at least in part, on determining a correlation between the adjusted sentiment and a focus area of the user with respect to the first user interface element and the second user interface element present on a display screen of the second device at a time the screenshot is captured.

### Claim 2 (depends on 1)

The method of claim 1, wherein the facial expression data is an image captured by a camera of the first mobile device.

### Claim 3 (depends on 1)

The method of claim 1, wherein the facial expression data is generated by one or more sensors in the first mobile device, wherein the one or more sensors includes at least one of an eye tracking sensor and a muscle movement sensor.

### Claim 4 (depends on 1)

The method of claim 1, wherein the screenshot is captured proximate in time to receiving the facial expression data.

### Claim 5 (depends on 1)

The method of claim 1, wherein the user focus area is determined, at least in part, by an eye tracking sensor.