IP Library Granted Patent US 10,311,139
Granted Patent B2
US 10,311,139 · App. 15/612,162 · Granted Jun 4, 2019

Systems and methods for identifying and suggesting emoticons

Inventors: Gabriel Leydon (Menlo Park, CA); Nikhil Bojja (Mountain View, CA)
Assignee: MZ IP Holdings, LLC
G06F17/24G06F3/0219G06F3/0238G06F17/241G06F17/274G06F17/2725G06F17/2775G06F17/2785G06Q30/0209G07F17/3244H04L51/04H04M1/72552
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,311,139
App. No.
15/612,162
Granted
Jun 4, 2019
Kind
B2
Abstract

Computer-implemented systems and methods are provided for suggesting emoticons for insertion into text based on an analysis of sentiment in the text. An example method includes: determining a first sentiment of text in a text field; selecting first text from the text field in proximity to a current position of an input cursor in the text field; identifying one or more candidate emoticons wherein each candidate emoticon is associated with a respective score indicating relevance to the first text and the first sentiment based on, at least, historical user selections of emoticons for insertion in proximity to respective second text having a respective second sentiment; providing one or more candidate emoticons having respective highest scores for user selection; and receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor.

Claims (59)

1. A computer-implemented method, comprising:

receiving text entered by a user;

determining a first sentiment of the text;

searching emoticons in a corpus of emoticons,

wherein each emoticon comprises a visual representation of the emoticon and is associated with a respective second sentiment;

identifying one of the emoticons as a candidate for insertion into the text based on a score indicating relevance between the first sentiment of the text and the respective second sentiment of the candidate emoticon;

providing the candidate emoticon for selection by the user;

receiving the selection of the candidate emoticon by the user; and

inserting the selected emoticon into the text.

2. The method of claim 1 , wherein the selected emoticon is inserted at a current position of an input cursor in the text.

3. The method of claim 1 , wherein providing the candidate emoticon for selection by the user comprises:

presenting the candidate emoticon for selection by the user at or near a current position of an input cursor in the text.

4. The method of claim 1 , comprising:

determining a respective popularity of the emoticons through crowd sourcing.

5. The method of claim 4 , wherein the score is based at least in part on the popularity of the candidate emoticon.

6. The method of claim 1 , comprising:

determining that the text is associated with a brand, a product, or a service; and, based thereon,

identifying the candidate emoticon for the brand, the product, or the service.

7. The method of claim 1 , comprising:

performing sentiment analysis to determine the first sentiment of the text.

8. The method of claim 7 , wherein performing sentiment analysis to determine the first sentiment of the text comprises:

analyzing the text in real-time as the text is being entered by the user.

9. The method of claim 1 , wherein the first sentiment is associated with an attitude of the user with respect to a topic described in the text.

10. A system, comprising:

a searchable corpus of emoticons; and

one or more computer processors programmed to perform operations comprising:

receiving text entered by a user;

determining a first sentiment of the text;

searching emoticons in the corpus,

wherein each emoticon comprises a visual representation of the emoticon and is associated with a respective second sentiment;

identifying one of the emoticons as a candidate for insertion into the text based on a score indicating relevance between the first sentiment of the text and the respective second sentiment of the candidate emoticon;

providing the candidate emoticon for selection by the user;

receiving the selection of the candidate emoticon by the user; and

inserting the selected emoticon into the text.

11. The system of claim 10 , wherein the selected emoticon is inserted at a current position of an input cursor in the text.

12. The system of claim 10 , wherein the operation of providing the candidate emoticon for selection by the user comprises:

presenting the candidate emoticon for selection by the user at or near a current position of an input cursor in the text.

13. The system of claim 10 , wherein the operations further comprise:

determining a respective popularity of the emoticons through crowd sourcing.

14. The system of claim 13 , wherein the score is based at least in part on the popularity of the candidate emoticon.

15. The system of claim 10 , wherein the operations further comprise:

determining that the text is associated with a brand, a product, or a service; and, based thereon,

identifying the candidate emoticon for the brand, the product, or the service.

16. The system of claim 10 , wherein the operations further comprise:

performing sentiment analysis to determine the first sentiment of the text.

17. The system of claim 16 , wherein the operation of performing sentiment analysis to determine the first sentiment of the text comprises:

analyzing the text in real-time as the text is being entered by the user.

18. The system of claim 10 , wherein the first sentiment is associated with an attitude of the user with respect to a topic described in the text.

19. The system of claim 10 , wherein the searchable corpus of emoticons comprises one or more user-defined emoticons, and wherein each user-defined emoticon comprises a visual representation of the user-defined emoticon and is associated with a respective natural language and respective text.

20. An article, comprising:

a non-transitory computer-readable medium having instructions stored thereon that when executed by one or more computer processors cause the computer processors to perform operations comprising:

receiving text entered by a user;

determining a first sentiment of the text;

searching emoticons in a corpus of emoticons,

wherein each emoticon comprises a visual representation of the emoticon and is associated with a respective second sentiment;

identifying one of the emoticons as a candidate for insertion into the text based on a score indicating relevance between the first sentiment of the text and the respective second sentiment of the candidate emoticon;

providing the candidate emoticon for selection by the user;

receiving the selection of the candidate emoticon by the user; and

inserting the selected emoticon into the text.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded May 19, 2020
From: COMERICA BANK
To: MZ IP HOLDINGS, LLC
Reel/Frame 052706/0899 →
RELEASE OF SECURITY INTEREST Recorded May 19, 2020
From: MGG INVESTMENT GROUP LP, AS COLLATERAL AGENT
To: MACHINE ZONE, INC.; SATORI WORLDWIDE, LLC; COGNANT LLC
Reel/Frame 052706/0917 →
SECURITY INTEREST Recorded May 22, 2018
From: MZ IP HOLDINGS, LLC
To: COMERICA BANK
Reel/Frame 046215/0207 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 29, 2018
From: MACHINE ZONE, INC.
To: MZ IP HOLDINGS, LLC
Reel/Frame 045786/0179 →
NOTICE OF SECURITY INTEREST -- PATENTS Recorded Feb 2, 2018
From: MACHINE ZONE, INC.; SATORI WORLDWIDE, LLC; COGNANT LLC
To: MGG INVESTMENT GROUP LP, AS COLLATERAL AGENT
Reel/Frame 045237/0861 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 7, 2017
From: LEYDON, GABRIEL; BOJJA, NIKHIL
To: MACHINE ZONE, INC.
Reel/Frame 043216/0170 →
Continuity (4)
Continuation 15174435 · Jun 6, 2016
Continuation 14718869 · May 21, 2015
Continuation 14324733 · Jul 7, 2014
Related Publication 20170270087A1 · Sep 21, 2017