DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on 03/14/2025, 03/14/2025, 02/24/2026, 07/17/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
3. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l) (1) - 706.02(l) (3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
4. Claims 1, 4, 6, 8, 10-17, 19 of the pending application 19/066801 filed on 02/08/2025 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims (1+8), 13, 15, 1, 4-7, 14, (15+16), 8, (1+8), (1+8) of the issued patent 11,468,883 respectively. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the pending application are similar in scope in comparison to the issued patent. Please see the table below for claim similarities for the independent claim. The pending application and the issued patent refer to the same method/system for determining whether a phrase of the plurality of phrases is a trend and recommending/displaying the trending to user. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the method/system for determining whether a phrase of the plurality of phrases is the trend and displaying the trending to user as recited in the issued patent 11,468,883 to determine whether a phrase of the plurality of phrases is a trend and recommending the trending to user as recited in the present application 19/066801.
Pending Application 19/066801
Issued Patent 11,468,883
1. A system comprising:
at least one processor;
at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items received from client devices associated with users, the content items being modified using the modifications that comprises a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words in the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.
8. The method of claim 1 further comprising:
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be displayed by the client device.
4. The system of claim 1, wherein the users are associated with a messaging system, and wherein the content items comprise messages sent between or among the users via the messaging system.
13. The method of claim 1, wherein the content items comprise messages sent to one or more other users of the messaging system.
6. The system of claim 1, wherein the operations further comprise:
adjusting the plurality of frequencies based on a number of external events.
15. The method of claim 1 further comprising: adjusting a value of the frequency based on a number of external events.
8. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend,
generating trend content items associated with the phrase, the trend content items being a text, an image, or an augmentation content.
1. A method comprising:
extracting modifications from content items received from client devices associated with users, the content items being modified using the modifications that comprises a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words in the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.
10. The system of claim 9, wherein the operations further comprise:
determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the phrase is the trend is further based on the average amount of time per user spent associated with the content items.
4. The method of claim 1 further comprising:
determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the one or more words is the trend is further based on the average amount of time per user spent associated with the content items.
11. The system of claim 10, wherein the operations further comprise:
determining a passion value for the phrase based on the average amount of time per user spent associated with the content items associated with the phrase and an average amount of time per user associated with all content items.
5. The method of claim 4 further comprising:
determining a passion value for the one or more words based on the average amount of time per user spent associated with the content items associated with the one or more words and an average amount of time per user associated with all content items.
12. The system of claim 1, wherein determining the plurality of frequencies further comprises:
determining the plurality of frequencies for the plurality of phrases further based on search logs, the search logs comprising saved records of search queries received from user devices in a messaging system.
6. The method of claim 1 further comprising:
determining the frequency of the one or more words in the content items, in the extracted modifications, and in search logs, the search logs being saved records of search queries received from client devices in the messaging system.
13. The system of claim 1, wherein the phrase is an n-gram, and wherein the one or more words is one to seven words.
7. The method of claim 1 wherein the one or more words is an n-gram, and wherein the one or more words is one to seven words.
14. The system of claim 1, wherein the operations further comprise:
determining the plurality of phrases from content components, wherein the content components comprise names of movies and names of computer games.
14. The method of claim 1 further comprising:
determining candidate one or more words from known content components, wherein the known content components comprise names of movies and names of computer games; and
determining the one or more words based on the candidate one or more words and from the content items and the extracted modifications.
15. The system of claim 1, wherein the operations further comprise:
adjusting values of the plurality of frequencies based on a number of external events, wherein a frequency is increased when an external event of the number of external events has a negative correlation with a corresponding phrase of the plurality of phrases and the frequency is decreased when the external event has a positive correlation with the corresponding phrase.
15. The method of claim 1 further comprising: adjusting a value of the frequency based on a number of external events.
16. The method of claim 15, wherein the frequency is increased when the external events have a negative correlation with the one or more words and the frequency is decreased when the external events have a positive correlation with the one or more words.
16. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend, recommending content items associated with the phrase to users of the user devices.
8. The method of claim 1 further comprising:
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be displayed by the client device.
17. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items received from client devices associated with users, the content items being modified using the modifications that comprises a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words in the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.
8. The method of claim 1 further comprising:
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be displayed by the client device.
19. A non-transitory machine-readable storage medium comprising instructions that, when executed by at least one processor of a machine, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items received from client devices associated with users, the content items being modified using the modifications that comprises a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words in the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.
8. The method of claim 1 further comprising:
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be displayed by the client device.
This is a non-provisional nonstatutory double patenting rejection because the patentably indistinct claims have in fact been patented.
5. Claims 1, 6-8, 10-17, and 20 of the pending application 19/066801 filed on 02/08/2025 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims (1+2), 17, 1, 3, 8-11, 16, (15+16), 8, (1+2), (1+2) of the issued patent 11,948,558 respectively. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the pending application are similar in scope in comparison to the issued patent. Please see the table below for claim similarities for the independent claim. The pending application and the issued patent refer to the same method/system for determining whether a phrase of the plurality of phrases is a trend and recommending/displaying the trending to user. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the method/system for determining whether a phrase of the plurality of phrases is the trend and displaying the trending to user as recited in the issued patent 11,948,558 to determine whether a phrase of the plurality of phrases is a trend and recommending the trending to user as recited in the present application 19/066801.
Pending Application 19/066801
Issued Patent 11,948,558
1. A system comprising:
at least one processor;
at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items accessed by client devices, the content items being modified by the modifications, the modifications comprising a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words from the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
2. The method of claim 1 further comprising: causing the report to be displayed on a display of a computing device.
6. The system of claim 1, wherein the operations further comprise:
adjusting the plurality of frequencies based on a number of external events.
17. The method of claim 1 further comprising: adjusting a value of the frequency based on a number of external events, wherein the frequency is increased when the external events have a negative correlation with the one or more words and the frequency is decreased when the external events have a positive correlation with the one or more words.
7. The system of claim 1, wherein the operations further comprise: in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
1. A method comprising:
extracting modifications from content items accessed by client devices, the content items being modified by the modifications, the modifications comprising a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words from the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
8. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend,
generating trend content items associated with the phrase, the trend content items being a text, an image, or an augmentation content.
3. The method of claim 1 further comprising: in response to the one or more words being determined as the trend, generating trend content items associated with the one or more words, the trend content being a text, an image, or an augmentation content.
10. The system of claim 9, wherein the operations further comprise:
determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the phrase is the trend is further based on the average amount of time per user spent associated with the content items.
8. The method of claim 7 further comprising: determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the one or more words is the trend is further based on the average amount of time per user spent associated with the content items.
11. The system of claim 10, wherein the operations further comprise:
determining a passion value for the phrase based on the average amount of time per user spent associated with the content items associated with the phrase and an average amount of time per user associated with all content items.
9. The method of claim 8 further comprising: determining a passion value for the one or more words based on the average amount of time per user spent associated with the content items associated with the one or more words and an average amount of time per user associated with all content items.
12. The system of claim 1, wherein determining the plurality of frequencies further comprises:
determining the plurality of frequencies for the plurality of phrases further based on search logs, the search logs comprising saved records of search queries received from user devices in a messaging system.
10. The method of claim 1 further comprising: determining the frequency of the one or more words in the content items, in the extracted modifications, the text labels, and in search logs, the search logs being saved records of search queries received from client devices in a messaging system.
13. The system of claim 1, wherein the phrase is an n-gram, and wherein the one or more words is one to seven words.
11. The method of claim 1 wherein the one or more words is an n-gram, and wherein the one or more words is one to seven words.
14. The system of claim 1, wherein the operations further comprise:
determining the plurality of phrases from content components, wherein the content components comprise names of movies and names of computer games.
16. The method of claim 1 further comprising:
determining candidate one or more words from known content components, wherein the known content components comprise names of movies and names of computer games; and
determining the one or more words based on the candidate one or more words and from the content items and the extracted modifications.
15. The system of claim 1, wherein the operations further comprise:
adjusting values of the plurality of frequencies based on a number of external events, wherein a frequency is increased when an external event of the number of external events has a negative correlation with a corresponding phrase of the plurality of phrases and the frequency is decreased when the external event has a positive correlation with the corresponding phrase.
17. The method of claim 1 further comprising: adjusting a value of the frequency based on a number of external events, wherein the frequency is increased when the external events have a negative correlation with the one or more words and the frequency is decreased when the external events have a positive correlation with the one or more words.
16. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend, recommending content items associated with the phrase to users of the user devices.
2. The method of claim 1 further comprising: causing the report to be displayed on a display of a computing device.
17. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items accessed by client devices, the content items being modified by the modifications, the modifications comprising a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words from the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
2. The method of claim 1 further comprising: causing the report to be displayed on a display of a computing device.
19. A non-transitory machine-readable storage medium comprising instructions that, when executed by at least one processor of a machine, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items accessed by client devices, the content items being modified by the modifications, the modifications comprising a text caption or a media overlay;
identifying objects within the content items;
assigning text labels to the objects;
determining one or more words from the content items and the extracted modifications;
determining a frequency of the one or more words from the content items, the extracted modifications, and the text labels;
determining whether the one or more words is a trend based on the frequency and an aggregate frequency; and
in response to the one or more words being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
2. The method of claim 1 further comprising: causing the report to be displayed on a display of a computing device.
This is a non-provisional nonstatutory double patenting rejection because the patentably indistinct claims have in fact been patented.
6. Claims 1, 5-8, 10-17, 19 of the pending application 19/066801 filed on 02/08/2025 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims (1+3), 2, 1, 1, 4, 9-12, 14-15, 18, (1+3), (1+3) of the issued patent 12,300,224 respectively. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the pending application are similar in scope in comparison to the issued patent. Please see the table below for claim similarities for the independent claim. The pending application and the issued patent refer to the same method/system for determining whether a phrase of the plurality of phrases is a trend and recommending/displaying the trending to user. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the method/system for determining whether a phrase of the plurality of phrases is the trend and displaying the trending to user as recited in the issued patent 12,300,224 to determine whether a phrase of the plurality of phrases is a trend and recommending the trending to user as recited in the present application 19/066801.
Pending Application 19/066801
Issued Patent 12,300,224
1. A system comprising:
at least one processor;
at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications, the modifications comprising at least one of: text caption or a media overlay;
determining a phrase for each of the content items and the extracted modifications to generate a plurality of phrases, wherein the phrase comprises one or more words;
determining frequencies for the plurality of phrases to generate a plurality of frequencies;
adjusting the plurality of frequencies based on a number of external events;
determining whether a phrase of the plurality of phrases is a trend based on the adjusted plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
3. The method of claim 2 further comprising: causing the report to be displayed on a display of a computing device.
5. The system of claim 1, wherein the phrase is a first phrase, and wherein the operations further comprise:
identifying objects within the content items;
assigning second phrases to the objects; and
adjusting the plurality of frequencies based on the second phrases.
2. The method of claim 1, wherein the phrase is a first phrase, and wherein the method further comprising:
identifying objects within the content items;
assigning second phrases to the objects; and
adjusting the adjusted plurality of frequencies based on the second phrases.
6. The system of claim 1, wherein the operations further comprise:
adjusting the plurality of frequencies based on a number of external events.
1. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications, the modifications comprising at least one of: text caption or a media overlay;
determining a phrase for each of the content items and the extracted modifications to generate a plurality of phrases, wherein the phrase comprises one or more words;
determining frequencies for the plurality of phrases to generate a plurality of frequencies;
adjusting the plurality of frequencies based on a number of external events;
determining whether a phrase of the plurality of phrases is a trend based on the adjusted plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
7. The system of claim 1, wherein the operations further comprise: in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
1. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications, the modifications comprising at least one of: text caption or a media overlay;
determining a phrase for each of the content items and the extracted modifications to generate a plurality of phrases, wherein the phrase comprises one or more words;
determining frequencies for the plurality of phrases to generate a plurality of frequencies;
adjusting the plurality of frequencies based on a number of external events;
determining whether a phrase of the plurality of phrases is a trend based on the adjusted plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
8. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend,
generating trend content items associated with the phrase, the trend content items being a text, an image, or an augmentation content.
4. The method of claim 1 further comprising: in response to the phrase being determined as the trend, generating trend content items associated with the phrase, the trend content items being a text, an image, or an augmentation content.
10. The system of claim 9, wherein the operations further comprise:
determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the phrase is the trend is further based on the average amount of time per user spent associated with the content items.
9. The method of claim 8 further comprising: determining an average amount of time per user of the users spent associated with the content items, wherein determining whether the phrase is the trend is further based on the average amount of time per user spent associated with the content items.
11. The system of claim 10, wherein the operations further comprise:
determining a passion value for the phrase based on the average amount of time per user spent associated with the content items associated with the phrase and an average amount of time per user associated with all content items.
10. The method of claim 9 further comprising: determining a passion value for the phrase based on the average amount of time per user spent associated with the content items associated with the phrase and an average amount of time per user associated with all content items.
12. The system of claim 1, wherein determining the plurality of frequencies further comprises:
determining the plurality of frequencies for the plurality of phrases further based on search logs, the search logs comprising saved records of search queries received from user devices in a messaging system.
11. The method of claim 1, wherein determining frequencies further comprises: determining frequencies for the plurality of phrases to generate a plurality of frequencies further based on search logs, the search logs comprising saved records of search queries received from user devices in a messaging system.
13. The system of claim 1, wherein the phrase is an n-gram, and wherein the one or more words is one to seven words.
12. The method of claim 1, wherein the phrase is an n-gram, and wherein the one or more words is one to seven words.
14. The system of claim 1, wherein the operations further comprise:
determining the plurality of phrases from content components, wherein the content components comprise names of movies and names of computer games.
14. The method of claim 1 further comprising: determining the plurality of phrases from content components, wherein the content components comprise names of movies and names of computer games.
15. The system of claim 1, wherein the operations further comprise:
adjusting values of the plurality of frequencies based on a number of external events, wherein a frequency is increased when an external event of the number of external events has a negative correlation with a corresponding phrase of the plurality of phrases and the frequency is decreased when the external event has a positive correlation with the corresponding phrase.
15. The method of claim 1, wherein adjusting the plurality of frequencies based on the number of external events further comprises:
adjusting values of the plurality of frequencies based on a number of external events, wherein a frequency is increased when an external event of the number of external events has a negative correlation with a corresponding phrase of the plurality of phrases and the frequency is decreased when the external event has a positive correlation with the corresponding phrase.
16. The system of claim 1, wherein the operations further comprise:
in response to the phrase being determined as the trend, recommending content items associated with the phrase to users of the user devices.
18. The system of claim 17, wherein the operations further comprise: causing the report to be displayed on a display of a computing device.
17. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
1. A method comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications, the modifications comprising at least one of: text caption or a media overlay;
determining a phrase for each of the content items and the extracted modifications to generate a plurality of phrases, wherein the phrase comprises one or more words;
determining frequencies for the plurality of phrases to generate a plurality of frequencies;
adjusting the plurality of frequencies based on a number of external events;
determining whether a phrase of the plurality of phrases is a trend based on the adjusted plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
19. A non-transitory machine-readable storage medium comprising instructions that, when executed by at least one processor of a machine, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.
19. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications, the modifications comprising at least one of: a text caption or a media overlay;
determining a phrase for each of the content items and the extracted modifications to generate a plurality of phrases, wherein the phrase comprises one or more words;
determining frequencies for the plurality of phrases to generate a plurality of frequencies;
adjusting the plurality of frequencies based on a number of external events;
determining whether a phrase of the plurality of phrases is a trend based on the adjusted plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, generating a report indicating the trend, and causing the report to be stored in a memory.
This is a non-provisional nonstatutory double patenting rejection because the patentably indistinct claims have in fact been patented.
Claim Rejections - 35 USC § 101
7. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
8. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
All the claims are directed towards the statutory category of a machine/apparatus or process.
Claim 1 recites
“1. A system comprising:
at least one processor;
at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and
in response to the phrase being determined as the trend, recommending modifications associated with the phrase to users.” as recited in Claim 1.
The independent Claims 1, 17 and 19 recite substantially the same concept but do so in the context of the system, the method and the non-transitory machine-readable storage medium.
The limitations recited in the independent claims as drafted cover a mental process. More specifically, the underlying abstract idea revolved around what happens once a human determines a trend and recommends the trend to somebody. For example, the human could extract modifications from content items, determine a plurality of phrases in the extracted modification, determines a plurality of frequencies for the plurality of phrases, determine whether a phrase of the plurality of frequencies is a trend based on the plurality of frequencies and an aggregate frequency, if yes, the human could recommend modifications to some people.
The judicial exception is not integrated into a practical application. Particularly, claims recite the additional limitations of at least one processor, at least one memory, user devices, a non-transitory machine-readable storage medium. The additional element(s) or combination of elements such as processor, memory, device, non-transitory machine-readable storage medium in the claim(s) other than the abstract idea per se amount(s) to no more than (i) mere instructions to implement the idea on a computer, and/or (ii) recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. There is no further improvement to the computing device other than determining a trend and recommending the trend to some people. The mere recitation of a memory and a processor and/or the like is akin of adding the word “apply it” and/or “use it” with a computer in conjunction with the abstract idea. The paragraphs [00110, 00111, and 00217] of the specification disclose “[00217] "Machine storage medium" refers to a single or multiple storage devices and media (e.g., a centralized or distributed database, and associated caches and servers) that store executable instructions, routines and data. The term shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media, including memory internal or external to processors. Specific examples of machine-storage media, computer- storage media and device-storage media include non-volatile memory, including by way of example semiconductor memory devices, e.g., erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGA, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto - optical disks; and CD-ROM and DVD-ROM disks The terms "machine-storage medium," "device-storage medium," "computer-storage medium" mean the same thing and may be used interchangeably in this disclosure. The terms "machine-storage media," "computer-storage media," and "device-storage media" specifically exclude carrier waves, modulated data signals, and other such media, at least some of which are covered under the term "signal medium.", [00110] The machine 600 may include processors 602, memory 604, and input/output I/O components 638, which may be configured to communicate with each other via a bus 640. The processors 602 may be termed computer processors, in accordance with some embodiments. In an example, the processors 602 (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) Processor, a Complex Instruction Set Computing (CISC) Processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 606 and a processor 610 that execute the instructions 608. The term "processor" is intended to include multi-core processors that may comprise two or more independent processors (sometimes referred to as "cores") that may execute instructions contemporaneously. Although FIG. 6 shows multiple processors 602, the machine 600 may include a single processor with a single-core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof, [00111] The memory 604 includes a main memory 612, a static memory 614, and a storage unit 616, both accessible to the processors 602 via the bus 640. The main memory 604, the static memory 614, and storage unit 616 store the instructions 608 embodying any one or more of the methodologies or functions described herein. The instructions 608 may also reside, completely or partially, within the main memory 612, within the static memory 614, within machine- readable medium 618 within the storage unit 616, within at least one of the processors 602 (e.g., within the Processor's cache memory), or any suitable combination thereof, during execution thereof by the machine 600.)
As filed in the specification, the computer is listed as a general-purpose computer and is mainly used as an application thereof. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using a computer is noted as a general computer. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
The dependent claims do not remedy the issues noted above. More specifically, claims 2, 18 and 20 define the modification associated with the phrase. There are no additional limitations presented. Claim 3 merely indicates the users are associated with the user devices. There are no additional limitations presented. Claim 4 defines the content items. There are no additional limitations presented. Claim 5 recites mental processes of identifying objects, assigning phrases to the object and adjusting the plurality of frequencies. There are no additional limitations presented. Claim 6 recites a mental process of adjusting the plurality of frequencies. There are no additional limitations presented. Claim 7 recites mental process of generating a report (e.g., writing a report), and storing the report (e.g., saving the report in the folder.) There are no additional limitations presented. The claim uses memory as a tool to perform the abstract idea of storing the report. See MPEP 2106.05(f). Claim 8 recites mental process of generating trend content. There are no additional limitations presented. Claim 9 indicates using the device to access the content item. Using device as a tool to perform an abstract idea of accessing the content item. Claim 10 recites mental process of determining an average amount of time per user spent. There are no additional limitations presented. Claim 11 recites mental process of determining a passion value for the phrase. There are no additional limitations presented. Claim 12 recites mental process of determining the plurality of frequencies for the plurality of phrases. There are no additional limitations presented. Claim 13 defines the phrase as an n-gram. There are no additional limitations presented. Claim 14 recites mental process of determining the plurality of phrases from names of movies and names of computer games. There are no additional limitations presented. Claim 15 recites mental process of adjusting values of the plurality of frequencies based on a number of external events. There are no additional limitations presented. Claim 16 recites mental process of recommending content items to users. There are no additional limitations presented.
For at least the supra provided reasons, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Allowable Subject Matter
9. Claims 1-20 are allowed in view of the prior art of record. However, the claims stand rejected under 101 Abstract idea and Double Patenting rejections, and for the application to pass to allowance these rejections need to be overcome.
The following is a statement of reasons for the indication of allowable subject matter: the prior art(s) taken alone or in combination fail(s) to teach the following element(s) in combination with the other recited elements in the claim(s).
“extracting modifications from content items accessed by user devices, the content items being modified by the modifications;
determining a plurality of phrases for the extracted modifications, wherein each phrase of the plurality of phrases comprises one or more words;
determining a plurality of frequencies for the plurality of phrases;
determining whether a phrase of the plurality of phrases is a trend based on the plurality of frequencies and an aggregate frequency; and” as recited in Claim 1.
Claims 17 and 19 recite similar features as Claim 1.
The closest prior arts found as follows.
a. Lancar (US 2017/0330292 A1.) In this reference, Lancar discloses a method/a system for generating trend content associated with one or more word (Lancar [0028] The trend monitor 9 receives electronic content or information about electronic content from one or more social media platforms. For example, trend monitor 9 receives posts shared by users using one or more social media web sites to exchange comments with friends and followers. The trend monitor 9 uses the received electronic content information about electronic content from social media to identify that media trends are occurring as they occur, [0028] the trend monitor 9 detects that a particular word or phrase is occurring with greater frequency in recent social media, e.g., in posts within the last hours or last 5 minutes, etc., [0044] Trend monitor 32 uses parser 33 to parse the social media feed to identify occurrences and frequencies of particular words and phrases and uses categories 34 to categories particular trends in the social media feed 31 using keywords.) To generate trend content, Lancar utilizes the frequency of the one or more words in the content items and the extracted modification. Lancar does not determine whether one or more words is a trend based on the adjusted frequency and an aggregate frequency. Thus, Lancar fails to teach and/or suggest the allowable subject matter noted above.
b. Danson et al. (US 2018/0032886 A1.) In this reference, Danson et al. disclose a method/a system for analyzing data trends (Danson et al. [0006] The present disclosure describes methods and systems of analyzing trends in data relationships. In a first aspect, the present disclosure encompasses a system for analyzing data relating to trends, which includes a processor, an analysis module, wherein the analysis module is a non-transitory computer readable medium operably connected to the processor, wherein the non-transitory computer readable medium comprises a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, wherein the plurality of instructions when executed: analyze a first plurality of communications occurring over a first time period; determine a first plurality of terms based on the analyzed first plurality of communications; analyze a second plurality of communications occurring over a second time period; determine a second plurality of terms based on the analyzed second plurality of communications; identify trending terms based on the determined first plurality of terms and the determined second plurality of terms; review the identified trending terms to determine at least one reason for use of the identified trending terms in the first time period, the second time period, or both; and communicate the identified trending terms and the at least one reason for use of the identified trending terms to a user, a display device configured to display the identified trending terms and the at least one reason for use of the identified trending terms to the user, and a routing engine configured to send an automated message to an external source based on the at least one reason for use of the identified trending terms.) Danson et al. identifies trending terms based on the determined first plurality of terms and the determined second plurality of terms. Danson does not determine whether the one or more words is a trend based on the adjusted frequency and an aggregate frequency. Thus, Danson et al. fails to teach and/or suggest the allowable subject matter noted above.
c. Olteanu et al. (US 2015/0186417 A1.) In this reference, Olteanu et al. disclose a method/a system for identifying the trending terms (Olteanu et al. [0006] Based on the local frequency of a term and the global frequency of a term, the social networking system determines if the term is a trending term. For example, a ratio of the local frequency of a term to the global frequency of the term is determined, and if the ratio is at least a threshold value, the term is identified as a trending term. Alternatively, a distribution of various terms in the location store across areas including different physical location descriptions is determined, and trending terms are identified as terms having at least a threshold density of occurrence in an area from the distribution, [0048] One or more trending terms in the identified entries are determined 515 based on a global frequency of each term in the identified entries within the location store 230 in its entirety and a local frequency of each term in the identified entries within the identified entries. A trending term is a term having a local frequency exceeding its global frequency by at least a threshold amount; hence, a trending term is a term having a threshold popularity relative to the identified area. For example, if the terms "Times" and "Square" appear more frequently in entries having physical locations within an area than in the location store 230 as a whole, the terms "Times" and "Square" are determined 515 to be trending terms for the area.) Olteanu et al. detects the trending terms by comparing the local frequency and the global frequency. Olteanu et al. does not determine whether one or more words from the modifications is a trend based on the frequency and an aggregate frequency. Thus, Olteanu et al. fails to teach and/or suggest the allowable subject matter noted above.
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to application’s disclosure. See PTO-892.
a. Santos (US 2021/0119951 A1.) In this reference, Santos discloses a method/a system for identifying trends in social networks.
b. Kumar et al. (US 2021/0051124 A1.) In this reference, Kumar discloses a method/a system for determining a plurality of trending topics.
c. Bostick et al. (US 2018/0077344 A1.) In this reference, Bosick et al. disclose a method/a system for identifying grouping trends.
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/THUYKHANH LE/Primary Examiner, Art Unit 2655
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