IP Library Granted Patent US 9,977,828
Granted Patent B2
US 9,977,828 · App. 14/037,562 · Granted May 22, 2018

Assisted memorizing of event-based streams of mobile content

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Quick Facts
Patent No.
US 9,977,828
App. No.
14/037,562
Granted
May 22, 2018
Kind
B2
Abstract

Handling event data received by a mobile device includes filtering out at least a subset of event data based on pre-determined filtering rules, forming groups of event data by grouping at least some of the event data that has not been filtered out based on pre-determined grouping rules, and storing, based on pre-determined auto-filing rules, at least one of: groups of event data and non-filtered event data that is not included with any groups of event data. The event data may include photos, videos, recorded voice notes, phone calls, voice mails, user location data, messaging data, calendar entries, email messages, wireless data transmissions, and/or events scheduled from software applications and online services. The filtering rules may be based on a filtering criteria such as time, location, keyword match, semantic similarity, and/or relations to known events.

Claims (56)

1. A method of handling event data received by a mobile device, comprising:

obtaining the event data from a plurality of applications;

generating a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules;

determining whether grouping candidate event data exists in the filtered set of event data;

in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applying the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and

in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, foregoing applying the pre-determined grouping rules to the filtered set of event data;

applying pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules:

automatically store a first portion of the filtered set of event data; and

generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored,

wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and

wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and,

displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data.

2. A method, according to claim 1 , wherein the event data include at least one of: photos, videos, recorded voice notes, phone calls, voice mails, user location data, messaging data, calendar entries, email messages, wireless data transmissions, and events scheduled from software applications and online services.

3. A method, according to claim 1 , wherein the pre-determined filtering rules are based on at least one filtering criteria selected from the group consisting of: time, location, keyword match, semantic similarity, and relations to known events.

4. A method, according to claim 3 , wherein the pre-determined filtering rules are based on at least two of the filtering criteria that are logically combined.

5. A method, according to claim 1 , further comprising:

discarding at least one of the one or more groups within the filtered set of event data based on the auto-filing rules.

6. A method, according to claim 5 , wherein discarding is performed periodically.

7. A method, according to claim 5 , wherein discarding is performed in response to more than a predetermined amount of event data being stored in a portion of the memory of the mobile device that is used to store the filtered set of event data.

8. A method, according to claim 1 , wherein the pre-determined grouping rules are based on at least one of: people, location, and timing.

9. A method, according to claim 1 , wherein the mobile device includes software that is one of: pre-loaded with the device, installed from an app store, and downloaded from a Web site.

10. A method, according to claim 1 , wherein the mobile device uses an operating system selected from the group consisting of: iOS, Android OS, Windows Phone OS, Blackberry OS and mobile versions of Linux OS.

11. A method, according to claim 1 , including:

detecting user input for at least one of:

storing first data from the remainder set of the event data;

deleting second data from the remainder set of the event data; or

grouping third data from the remainder set of the event data with previously stored event data.

12. A method, according to claim 1 , wherein determining whether grouping candidate event data exists in the filtered set of event data includes determining whether the filtered set of event data includes data that corresponds to at least one event.

13. Computer software, provided in a non-transitory computer-readable medium, that handles event data received by a mobile device, the software comprising:

executable code that obtains the event data from a plurality of applications;

executable code that generates a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules;

executable code for determining whether grouping candidate event data exists in the filtered set of event data;

executable code that, in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applies the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and

executable code that, in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, forgoes applying the pre-determined grouping rules to the filtered set of event data;

executable code that applies pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules:

automatically store a first portion of the filtered set of event data; and

generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored,

wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and

wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and,

executable code for displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data.

14. Computer software, according to claim 13 , wherein the event data include at least one of: photos, videos, recorded voice notes, phone calls, voice mails, user location data, messaging data, calendar entries, email messages, wireless data transmissions, and events scheduled from software applications and online services.

15. Computer software, according to claim 13 , wherein the pre-determined filtering rules are based on at least one filtering criteria selected from the group consisting of: time, location, keyword match, semantic similarity, and relations to known events.

16. Computer software, according to claim 15 , wherein the pre-determined filtering rules are based on at least two of the filtering criteria that are logically combined.

17. Computer software, according to claim 13 , further comprising:

executable code that discards at least one of the one or more groups within the filtered set of event data some of the groups of event data and non-filtered event data that is not included with any groups of event data that are not stored based on the auto-filing rules.

18. Computer software, according to claim 17 , wherein discarding is performed periodically.

19. Computer software, according to claim 17 , wherein discarding is performed in response to more than a predetermined amount of event data being stored in a portion of the memory of the mobile device that is used to store the filtered set of event data.

20. Computer software, according to claim 13 , wherein the pre-determined grouping rules are based on at least one of: people, location, and timing.

21. Computer software, according to claim 13 , wherein the software is one of: pre-loaded with the mobile device, installed from an app store, and downloaded from a Web site.

22. Computer software, according to claim 13 , wherein the mobile device uses an operating system selected from the group consisting of: iOS, Android OS, Windows Phone OS, Blackberry OS and mobile versions of Linux OS.

23. Computer software, according to claim 13 , including:

executable code for detecting user input for at least one of:

storing at least a portion of the remainder set of the event data;

deleting at least a portion of the remainder set of the event data; or

grouping at least a portion of the remainder set of the event data with previously stored event data.

24. Computer software, according to claim 13 , wherein determining whether grouping candidate event data exists in the filtered set of event data includes determining whether the filtered set of event data includes data that corresponds to at least one event.

Assignments (10)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 12, 2024
From: EVERNOTE CORPORATION
To: BENDING SPOONS S.P.A.
Reel/Frame 066288/0195 →
RELEASE OF SECURITY INTEREST Recorded Mar 17, 2023
From: MUFG BANK, LTD.
To: EVERNOTE CORPORATION
Reel/Frame 063116/0260 →
RELEASE OF SECURITY INTEREST Recorded Oct 8, 2021
From: EAST WEST BANK
To: EVERNOTE CORPORATION
Reel/Frame 057852/0078 →
SECURITY INTEREST Recorded Oct 6, 2021
From: EVERNOTE CORPORATION
To: MUFG UNION BANK, N.A.
Reel/Frame 057722/0876 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT TERMINATION AT R/F 040192/0720 Recorded Oct 22, 2020
From: SILICON VALLEY BANK
To: EVERNOTE CORPORATION
Reel/Frame 054145/0452 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT TERMINATION AT R/F 040240/0945 Recorded Oct 22, 2020
From: HERCULES CAPITAL, INC.
To: EVERNOTE CORPORATION; EVERNOTE GMBH
Reel/Frame 054213/0234 →
SECURITY INTEREST Recorded Oct 19, 2020
From: EVERNOTE CORPORATION
To: EAST WEST BANK
Reel/Frame 054113/0876 →
SECURITY INTEREST Recorded Oct 5, 2016
From: EVERNOTE CORPORATION; EVERNOTE GMBH
To: HERCULES CAPITAL, INC., AS AGENT
Reel/Frame 040240/0945 →
SECURITY AGREEMENT Recorded Sep 30, 2016
From: EVERNOTE CORPORATION
To: SILICON VALLEY BANK
Reel/Frame 040192/0720 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 13, 2013
From: GARG, HEMANT; KITAINIK, LEONID
To: EVERNOTE CORPORATION
Reel/Frame 031589/0761 →