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 .
2. Claims 1-20 are pending in this office action. This action is responsive to Applicant’s application filed 02/14/30/2025.
Priority
Applicant’s claim for the benefit of a Continuation of 18/543813 , filed 12/18/2023 ,now U.S. Patent # 12,259,927 is acknowledged.
Since the Continuation application relied on part of the priority document (Continuation), the claim of priority will be considered on a claim-by-claim basis. The priority date of the instant application is at least 02/14/2025 (the filing date), but depending upon the specific material claimed, could be as early as 12/18/2023.
Information Disclosure Statement
4. The references listed in the IDS filed 03/19/2025 has been considered. A copy of the signed or initialed IDS is hereby attached.
Double Patenting
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 obviousness-type 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); and 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 a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
5. Claims 1-20 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,259,927. Although the conflicting claims are not identical, they are not patentably distinct from each other because they are substantially similar in scope and they use the same limitations.
The following table shows the claims 1-20 in Instant Application that are rejected by corresponding claim(s) 1-7 in US Patent No. 12,259,927.
Instant Application
US 12,259,927
A system for network management comprising processing circuitry coupled to computer-readable media, wherein the processing circuitry is configured to:
based on a change to a network prior to a first time, generate one or more first objects of a plurality of objects, the one or more first objects storing an intent graph model associated with the first time;
determine one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
apply the one or more changes to the intent graph model associated with the first time to generate the intent graph model representing a change to the network associated with a requested time, the first time different from the requested time; and
output an indication of the intent graph model associated with the requested time.
2. The system of claim 1, wherein to output the indication, the processing circuitry is configured to generate data for a user interface configured to present the intent graph model associated with the requested time.
3. The system of claim 1, wherein the one or more changes occur one or more times after the first time and at or before the requested time.
4. The system of claim 1, wherein the plurality of objects store at least one of system information describing one or more nodes of the network or interface information describing one or more interfaces of the network.
5. The system of claim 4, wherein a first object of the one or more first objects stores the system information and a second object of the one or more first objects stores the interface information.
6. The system of claim 4, wherein the one or more first objects store interface information and the one or more changes specify a change to the interface information stored by the one or more first objects.
7. The system of claim 1, wherein the processing circuitry is further configured to:
obtain tree information corresponding to the requested time, the tree information comprising one or more first pointers indicating the one or more first objects and one or more second pointers indicating the one or more second objects;
determine, based on the one or more first pointers, a first portion of the tree information that includes the intent graph model associated with the first time to determine the one or more first objects; and
wherein to determine the one or more second objects, the processing circuitry is configured to determine, based on the one or more second pointers, a second portion of the tree information that includes the one or more changes.
8. The system of claim 1, wherein the processing circuitry is further configured to:
store, using one or more third objects, a previous intent graph model associated with a previous time that occurs prior to the first time;
store, using one or more fourth objects, difference information indicating one or more second changes to the previous intent graph model that occurred after the previous time and no later than the first time;
determine an amount of data used to store the one or more fourth objects; and
wherein the processing circuitry is configured to generate the one or more first objects based on the change and the amount of data exceeding a threshold size.
9. The system of claim 1, wherein a quantity of a plurality of changes in a subset of the plurality of objects represents the change to the network prior to the first time, the subset excluding the one or more first objects and the one or more second objects.
10. The system of claim 1, wherein the one or more changes comprises a change to one or more of:
a network device in the network; or
a communication link in the network.
11. The system of claim 1, further comprising memory, wherein to apply the one or more changes the processing circuitry is further configured to:
store the one or more first objects in the memory;
store the one or more second objects in the memory; and
modify the one or more first objects in the memory using the one or more second objects in the memory to generate the intent graph model associated with the requested time in the memory.
12. The system of claim 11, wherein the processing circuitry is further configured to:
determine one or more third objects storing difference information indicating one or more additional changes to the intent graph model associated with the first time that occurred at a second time after the one or more changes and before the requested time;
apply the one or more additional changes to the intent graph model associated with the first time to generate an intent graph model associated with the second time; and
output an indication of the intent graph model associated with the second time.
13. A method comprising:
based on a change to a network prior to a first time, generating, by processing circuitry, one or more first objects of a plurality of objects representing a plurality of intent graph models of the network, the one or more first objects storing an intent graph model associated with the first time;
determining, by the processing circuitry, one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
applying, by the processing circuitry, the one or more changes to the intent graph model associated with the first time to generate the intent graph model representing a change to the network associated with a requested time, the first time different from the requested time; and
outputting, by the processing circuitry, an indication of the intent graph model associated with the requested time.
14. The method of claim 13, wherein outputting the indication comprises generating data for a user interface configured to present the intent graph model associated with the requested time.
15. The method of claim 13, wherein the one or more changes occur one or more times are after the first time and at or before the requested time.
16. The method of claim 13, wherein the plurality of objects store at least one of system information describing one or more nodes of the network or interface information describing one or more interfaces of the network.
17. The method of claim 16, wherein the one or more first objects of the plurality of objects store interface information and the one or more changes specify a change to the interface information stored by the one or more first objects.
18. The method of claim 13, further comprising:
obtaining, by the processing circuitry, tree information corresponding to the requested time, the tree information comprising one or more first pointers indicating the one or more first objects and one or more second pointers indicating the one or more second objects; determining, based on the one or more first pointers, a first portion of the tree information that includes the intent graph model associated with the first time to determine the one or more first objects; and
wherein determining the one or more second objects comprises determining, based on the one or more second pointers, a second portion of the tree information that includes the one or more changes.
19. The method of claim 13, further comprising determining, by the processing circuitry, one or more third objects storing difference information indicating one or more additional changes to the intent graph model associated with the first time that occurred at a second time after the one or more changes and before the requested time;
applying, by the processing circuitry, the one or more additional changes to the intent graph model associated with the first time to generate an intent graph model associated with the second time; and
outputting, by the processing circuitry, an indication of the intent graph model associated with the second time.
20. Non-transitory computer-readable storage media storing instructions that, when executed, cause processing circuitry to:
based on a change to a network prior to a first time, generate one or more first objects of a plurality of objects representing a plurality of intent graph models of the network, the one or more first objects storing an intent graph model associated with the first time;
determine one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
apply the one or more changes to the intent graph model associated with the first time to generate the intent graph model representing a change to the network associated with a requested time, the first time different from the requested time; and
output an indication of the intent graph model associated with the requested time.
1. A system for network management comprising:
computer-readable media configured to store a plurality of objects representing a plurality of intent graph models of a network; and
processing circuitry coupled to the computer-readable media, wherein the processing circuitry is configured to:
based on an amount of change to the network prior to a first time exceeding a threshold value, generate one or more first objects of the plurality of objects, the one or more first objects storing an intent graph model associated with the first time;
receive a request indicating an intent graph model associated with a requested time;
determine the one or more first objects of the plurality of objects, the first time different from the requested time;
determine one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
apply the one or more changes to the intent graph model associated with the first time to generate the intent graph model associated with the requested time; and
output an indication of the intent graph model associated with the requested time.
2. The system of claim 1, wherein to output the indication, the processing circuitry is configured to generate data for a user interface configured to present the intent graph model associated with the requested time.
3. The system of claim 1, wherein the one or more changes occur one or more times after the first time and at or before the requested time.
4. The system of claim 1, wherein the plurality of objects store at least one of system information describing one or more nodes of the network or interface information describing one or more interfaces of the network.
5. The system of claim 4, wherein a first object of the one or more first objects stores the system information and a second object of the one or more first objects stores the interface information.
6. The system of claim 4, wherein the one or more first objects store interface information and the one or more changes specify a change to the interface information stored by the one or more first objects.
7. The system of claim 1, wherein the processing circuitry is further configured to:
obtain tree information corresponding to the requested time, the tree information comprising one or more first pointers indicating the one or more first objects and one or more second pointers indicating the one or more second objects;
wherein to determine the one or more first objects, the processing circuitry is configured to determine, based on the one or more first pointers, a first portion of the tree information that includes the intent graph model associated with the first time; and
wherein to determine the one or more second objects, the processing circuitry is configured to determine, based on the one or more second pointers, a second portion of the tree information that includes the one or more changes.
8. The system of claim 1, wherein the processing circuitry is further configured to:
store, using one or more third objects, a previous intent graph model associated with a previous time that occurs prior to the first time;
store, using one or more fourth objects, difference information indicating one or more second changes to the previous intent graph model that occurred after the previous time and no later than the first time; and
determine an amount of data used to store the one or more fourth objects,
wherein the amount of data represents the amount of change and a size of the amount of data exceeds the threshold value.
9. The system of claim 1, wherein a quantity of a plurality of changes in a subset of the plurality of objects represents the amount of change and exceeds the threshold value, the subset excluding the one or more first objects and the one or more second objects.
10. The system of claim 1, wherein the one or more changes comprises a change to one or more of:
a node in the network; or
a link in the network.
11. The system of claim 1, further comprising memory, wherein to apply the one or more changes the processing circuitry is further configured to:
store the one or more first objects in the memory;
store the one or more second objects in the memory; and
modify the one or more first objects in the memory using the one or more second objects in the memory to generate the intent graph model associated with the requested time in the memory.
12. The system of claim 11, wherein the processing circuitry is further configured to:
determine one or more third objects storing difference information indicating one or more additional changes to the intent graph model associated with the first time that occurred at a second time after the one or more changes and before the requested time;
apply the one or more additional changes to the intent graph model associated with the first time to generate an intent graph model associated with the second time; and
output an indication of the intent graph model associated with the second time.
13. A method for network management comprising:
based on an amount of change to a network prior to a first time exceeding a threshold value, generating, by processing circuitry, one or more first objects of a plurality of objects representing a plurality of intent graph models of the network, the one or more first objects storing an intent graph model associated with the first time;
receiving, by the processing circuitry, a request indicating an intent graph model associated with a requested time;
determining, by the processing circuitry, the one or more first objects of a plurality of objects, the first time different from the requested time;
determining, by the processing circuitry, one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
applying, by the processing circuitry, the one or more changes to the intent graph model associated with the first time to generate the intent graph model associated with the requested time; and
outputting, by the processing circuitry, an indication of the intent graph model associated with the requested time.
14. The method of claim 13, wherein outputting the indication comprises generating data for a user interface configured to present the intent graph model associated with the requested time.
15. The method of claim 13, wherein the one or more changes occur one or more times are after the first time and at or before the requested time.
16. The method of claim 13, wherein the plurality of objects store at least one of system information describing one or more nodes of the network or interface information describing one or more interfaces of the network.
17. The method of claim 16, wherein the one or more first objects of the plurality of objects store interface information and the one or more changes specify a change to the interface information stored by the one or more first objects.
18. The method of claim 13, further comprising:
obtaining, by the processing circuitry, tree information corresponding to the requested time, the tree information comprising one or more first pointers indicating the one or more first objects and one or more second pointers indicating the one or more second objects;
wherein determining the one or more first objects comprises determining, based on the one or more first pointers, a first portion of the tree information that includes the intent graph model associated with the first time; and
wherein determining the one or more second objects comprises determining, based on the one or more second pointers, a second portion of the tree information that includes the one or more changes.
19. The method of claim 13, further comprising determining, by the processing circuitry, one or more third objects storing difference information indicating one or more additional changes to the intent graph model associated with the first time that occurred at a second time after the one or more changes and before the requested time;
applying, by the processing circuitry, the one or more additional changes to the intent graph model associated with the first time to generate an intent graph model associated with the second time; and
outputting, by the processing circuitry, an indication of the intent graph model associated with the second time.
20. Non-transitory computer-readable storage media storing instructions that, when executed, cause processing circuitry of a network management system to:
based on an amount of change to a network prior to a first time exceeding a threshold value, generate one or more first objects of a plurality of objects representing a plurality of intent graph models of the network, the one or more first objects storing an intent graph model associated with the first time;
receive a request indicating an intent graph model associated with a requested time;
determine the one or more first objects of a plurality of objects, the first time different from the requested time;
determine one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time;
apply the one or more changes to the intent graph model associated with the first time to generate the intent graph model associated with the requested time; and
output an indication of the intent graph model associated with the requested time.
Although the conflicting claims are not identical, they are not patentably distinct from each other because they are substantially similar in scope and they use the same limitations.
After analyzing the language of the claims, it is clear that claims 1-20 are merely an obvious variation of claims 1-20 of US Patent No. 12,259,927. It is clear that under the broadest reasonable interpretation of the claims. Therefore, these two sets of claims are not patentably distinct.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims under 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of 35 U.S.C. 103(c) and potential 35 U.S.C. 102(e), (f) or (g) prior art under 35 U.S.C. 103(a).
5. Claims 1-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Rizk et al. (US, 2024/0265210, hereinafter “Rizk”) in view of Kahn et al. (US Patent Publication No. 2024/0095544 A1, hereinafter “Kahn”).
As to Claim 1, Rizk teaches the claimed limitations:
“A system for network management comprising processing circuitry coupled to computer-readable media, wherein the processing circuitry is configured to:” as a computer program product includes one or more computer readable storage mediums having program instructions. The program instructions are executable by one or more processors to cause the one or more processors to execute operations. The executable operations include receiving a plurality of input conversations (paragraph 0008).
“based on a change to a network prior to a first time, generate one or more first objects of a plurality of objects, the one or more first objects storing an intent graph model associated with the first time” as a meta intent generation (MIG) framework includes classifier conversations classified conversations, masked utterances, generalized intents, feature vectors, conversation similarity metric, and meta intent model. The elements are examples of data structures that may be created, stored, accessed, executed, or otherwise utilized in performing the operations (paragraph 0049). MIG framework generates generalized intents by performing entity recognition. More particularly, entity recognizer is capable of processing classified conversations using knowledge graph to generate generalized intents. Knowledge graph, which may be referred to as a semantic network, may be implemented as a data structure that represents or specifies a network of real-world entities. Examples of the real-world entities that may be specified by a knowledge graph include objects, events, situations, or concepts. Knowledge graph illustrates the relationship between these real-world entities (paragraphs 0055, 0078-0080).
“determine one or more second objects of the plurality of objects, the one or more second objects storing difference information indicating one or more changes to the intent graph model associated with the first time that occurred after the first time” as by determining which of the received task-oriented conversations are similar, meta intent generation (MIG) is capable of generating a meta intent model in which multiple different conversations may be generalized to the same meta intent, as generated specifies a hierarchy of related intents and corresponding slots, the resulting meta intent model may be used by a conversational automation agent to process different task-oriented conversations. A first user may say please help me look for flights from Boston to Florida on 1.sup.st July (e.g., the first time). A second user may say I need to book trains between Boston and Albany (e.g., the second time). While the two conversations specify different types of travel and different cities, both may be generalized to a meta intent such as booking a trip. In accordance with the inventive arrangements, the resulting meta intent model, when used by a conversational automation agent, is capable of processing both requests as different instances. Use of the meta intent model allows the conversational automation agent to obtain information from the user to perform a meta intent in less time (e.g., in fewer turns and with less duplication/redundancy in the conversation with the user) and using fewer computational resources of computer (paragraph 0032). How a conversational automation agent may use meta intent model in real time to process user conversations. The conversational automation agent is capable of traversing meta intent model while processing received user utterances to determine the particular complex task being requested and the information that is needed. In traversing meta intent model, the conversational automation agent may move from leaves to the root or vice versa depending on the particular user utterances received and the ordering of such user utterance (paragraphs 0078-0080).
“apply the one or more changes to the intent graph model associated with the first time to generate the intent graph model representing a change to the network associated with a requested time, the first time different from the requested time” as the entity recognizer is configured to apply a knowledge graph to the plurality of intents and slots. Slots of the plurality of input conversations as classified are masked to generate masked utterances. conversational data (abstract). Determining a plurality of intents and slots from the plurality of input conversations by processing the plurality of input conversations through a first classifier; generating a plurality of generalized intents by performing entity recognition on the plurality of intents and slots using an entity recognizer configured to apply a knowledge graph to the plurality of intents and slots; masking slots of the plurality of input conversations as classified to generate masked utterances; encoding conversational data as a plurality of feature vectors, wherein the conversational data includes the masked utterances and the plurality of generalized intents; and generating a meta intent model by processing the plurality of feature vectors corresponding to the plurality of input conversations through a second classifier using a conversation similarity metric (paragraph 0078, claim 17).
Rizk does not explicitly teach the claimed limitation “output an indication of the intent graph model associated with the requested time“.
Kahn teaches a method includes receiving a user input by a user from a client system associated with the user at a current time, parsing the user input to identify intents and slots associated with the user input, determining that one or more of the identified intents or slots are volatile based on whether the respective intent or slot resolves to information that is subject to change within a threshold timeframe of the current time, requesting information from an agent to resolve the user input (abstract). The assistant system may perform concierge-type services or provide information based on the user input. The assistant system may be performed by an assistant system may include schedule management (paragraph 0003). The assistant system may generate responses to requests related to volatile subjects (i.e., subjects where the answer may change rapidly or unexpectedly within a particular timeframe), if the querying user were to ask, what is traffic like to get home right now? the assistant system may reply back with Traffic is light right now. It will take you 30 minutes to get home. However, depending on the time of day, this information may change in a relatively short timeframe (paragraph 0007). The output of the task completion module may select action. Meanwhile, the dialog engine may receive an instruction to update the dialog state. The update may comprise awaiting agents' response, the CU composer may generate a communication content for the user using the NLG based on the output of the task completion module. The CU composer may also determine a modality of the generated communication content using the user interface payload generator. Since the generated communication content may be considered as a response to the user request, the CU composer may additionally rank the generated communication content using a response ranker, the ranking may indicate the priority of the response (paragraph 0045, 0059).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, having the teachings of Rizk and Kahn before him/her, to modify Rizk output an indication of the intent graph model associated with the requested time because that would provide a social-networking system to facilitate social interaction between or among users as taught by Kahn (paragraph 0004).
As to Claim 2, Rizk teaches the claimed limitations:
“wherein to output the indication, the processing circuitry is configured to generate data for a user interface configured to present the intent graph model associated with the requested time” as (paragraphs 0053-0054, 0072, 0089-0092).
Kahn teaches (abstract, paragraphs 0003, 0007-0008, 0045, 0059).
As to Claim 3, Rizk teaches the claimed limitations:
“wherein the one or more changes occur one or more times after the first time and at or before the requested time” as (paragraphs 0024, 0027, 0032, 0078-0079).
Kahn teaches (abstract, paragraphs 0003, 0007, 0042-0045).
As to Claim 4, Rizk teaches the claimed limitations:
“Wherein the plurality of objects store at least one of system information describing one or more nodes of the network or interface information describing one or more interfaces of the network” as (paragraphs 0018, 0055,0060-0062, 0069-0072).
Kahn teaches (paragraphs 0005, 0026, 0030-0031, 0035-0036).
As to Claim 5, Rizk teaches the claimed limitations:
“Wherein a first object of the one or more first objects stores the system information and a second object of the one or more first objects stores the interface information” as (paragraphs 0028, 0032-0037, 0039-0041, 0044-0045, 0055).
Kahn teaches (paragraphs 0003-0007, 0023, 0029-0034).
As to Claim 6, Rizk teaches the claimed limitations:
“Wherein the one or more first objects store interface information and the one or more changes specify a change to the interface information stored by the one or more first objects” as (paragraphs 0033, 0039, 0041).
Kahn teaches (paragraphs 0003-0006, 0029-0033, 0036-0039).
As to Claim 7, Rizk teaches the claimed limitations:
“wherein the processing circuitry is further configured to: obtain tree information corresponding to the requested time, the tree information comprising one or more first pointers indicating the one or more first objects and one or more second pointers indicating the one or more second objects; determine, based on the one or more first pointers, a first portion of the tree information that includes the intent graph model associated with the first time to determine the one or more first objects; and wherein to determine the one or more second objects, the processing circuitry is configured to determine, based on the one or more second pointers, a second portion of the tree information that includes the one or more changes” as (paragraphs 0017, 0030, 0032, 0056, 0060, 0062, 0069-0078, 0091).
Kahn teaches (abstract, paragraphs 0056, 0065, 0073).
As to Claim 8, Rizk teaches the claimed limitations:
“wherein the processing circuitry is further configured to: store, using one or more third objects, a previous intent graph model associated with a previous time that occurs prior to the first time; store, using one or more fourth objects, difference information indicating one or more second changes to the previous intent graph model that occurred after the previous time and no later than the first time; determine an amount of data used to store the one or more fourth objects; and wherein the processing circuitry is configured to generate the one or more first objects based on the change and the amount of data exceeding a threshold size” as (paragraphs 0038, 0061, 0078).
Kahn teaches (abstract, paragraphs 0003, 0008, 0035, 0053, 0064-0065, 0072-0073, 0077, 0080, 0096, 0107-0108).
As to Claim 9, Rizk teaches the claimed limitations:
“Wherein the processing circuitry is further configured to generate the one or more first objects when a quantity of a plurality of changes in a subset of the plurality of objects exceeds a threshold value, the subset excluding the one or more first objects and the one or more second objects” as (paragraphs 0018, 0060-0061, 0064, 0053-0054, 0072-0073).
Kahn teaches (abstract, paragraphs 0008, 0035, 0045, 0053-0055, 0064-0065, 0072-0073, 0077, 0080,0090, 0093, 0096, 0108).
As to Claim 10, Rizk teaches the claimed limitations:
“Wherein the one or more changes comprises a change to one or more of: a node in the network; or a link in the network” as (paragraphs 0018, 0060-0061, 0069, 0072).
Kahn teaches (paragraphs 0023, 0032, 0035-0036, 0079).
As to Claim 11, Rizk teaches the claimed limitations:
“Memory, wherein to apply the one or more changes the processing circuitry is further configured to: store the one or more first objects in the memory; store the one or more second objects in the memory; modify the one or more first objects in the memory using the one or more second objects in the memory to generate the intent graph model associated with the requested time in the memory” as (paragraphs 0008, 0049, 0055, claim 17).
Kahn teaches (paragraphs 0004-0006, 0029, 0035, 0037, 0039-0040, 0052-0055, 0060, 0065, 0077, 0082).
As to Claim 12, Rizk teaches the claimed limitations:
“wherein the processing circuitry is further configured to: determine one or more third objects storing difference information indicating one or more additional changes to the intent graph model associated with the first time that occurred at a second time after the one or more times and before the requested time; apply the one or more additional changes to the intent graph model associated with the first time to generate an intent graph model associated with the second time; and output an indication of the intent graph model associated with the second time” as (paragraphs 0028, 0056, 0060-0062, 0072).
Kahn teaches (paragraphs 0053, 0108).
As to claims 13-19 are rejected under 35 U.S.C 103(a), the limitations therein have substantially the same scope as claims 1-4, 6-7, and 12. In addition, Rizk teaches the method includes determining, by the computer hardware, a plurality of intents and slots from the plurality of input conversations by processing the plurality of input conversations through a first classifier (paragraph 0006). Therefore, these claims are rejected for at least the same reasons as claims 1-4, 6-7, and 12.
As to claim 20 is rejected under 35 U.S.C 103(a), the limitations therein have substantially the same scope as claim 1. In addition, Rizk teaches a computer program product includes one or more computer readable storage mediums having program instructions. The program instructions are executable by one or more processors to cause the one or more processors to execute operations. The executable operations include receiving a plurality of input conversations (paragraph 0008). Therefore, this claim is rejected for at least the same reasons as claim 1.
Examiner’s Note
Examiner has cited particular columns/paragraph and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131(b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as “Applicants believe no new matter has been introduced” may be deemed insufficient.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James Hwa whose telephone number is 571-270-1285 or email address james.hwa@uspto.gov. The examiner can normally be reached on 9:00 am – 5:30 pm EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ajay Bhatia can be reached on 571-272-3906. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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01/28/2026
/SHYUE JIUNN HWA/
Primary Examiner, Art Unit 2156