DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim status
Claims 1-20 presented for the examination and remain pending in the application.
Information Disclosure Statement
The Information Disclosure Statement (IDS) submitted on 09/16/2026 has been considered by the Examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are processing unit configured to “obtain…”, “determine…”, in claim 1, and in claim 10 processing unit configured to “cause…” and further in claim 16 processing unit configured to “provide…”. These limitations are being treated as a 112f limitations, because it meets the 3-prong test to determine when limitations are a 112f limitation. First, the term “processing unit” is a substitute or placeholder for “means”. Second, it is modified by functional language, “configured to: “obtain…”, “determine…”, “cause…” and “provide…”. Third, they are not modified by sufficient structure, material, or acts for performing the claimed functions.
Because this claims 1, 10 and 16 limitations are being interpreted under 35 U.S.C. 112(f) or pre-
AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure
described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-
AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them
being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting
sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim
limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being
interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
A review of the specification shows that the following appear to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre- AIA 35 U.S.C. 112, sixth paragraph limitations and there is no disclosure of any particular structure or corresponding algorithms for these limitations to perform the claimed limitations and thus, the limitations “processing unit configured to: “obtain…”, “determine…”, “cause…” and “ provide…” in claims 1, 10 and 16 are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A 35 U.S.C. 112(f) ("means-plus-function") claim limitation, if it fails to be supported by corresponding structure, material, or acts in the specification, necessitates a 112(b) rejection because it renders the claim indefinite. It is open ended.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 10 and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1. 10 and 16 recite in the limitations processing unit configured to “obtain…”, “determine…”, in claim 1, and in claim 10 processing unit configured to “cause…” and further in claim 16 processing unit configured to “provide…”. invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts to performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification is devoid of adequate structure to perform the claimed function. In particular, the specification states the claimed function of creating and maintaining multiple network connections performed by a plurality of network interfaces. There is no disclosure of any particular structure, either explicitly or inherently, to perform the recited function and nowhere in the specification indicated that “processing unit configured to “obtain…”, “determine…”, in claim 1, processing unit configured to “cause…” in claim 10 and further processing unit configured to “provide…”in claim 16.” coupled with a corresponding structure element such as CPU or hardware device in order to perform the claimed functions.
Therefore, the claims are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Dependent claims 2-9, 11-15 and 18 are also rejected because directly or indirectly depend on the rejected independent claim 1.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 10 and 16 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. As described above, the claimed elements in the limitations such as “processing unit configured to “obtain…”, “determine…”, “cause…” and “provide…” do not provide adequate structure to perform the claimed function. The specification does not demonstrate that that applicant has made an invention that achieves the claimed function because the invention is not described with sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor had possession of claimed invention.
Dependent claims 2-9, 11-15 and 18 are also rejected because directly or indirectly depend on the rejected independent claim 1.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 2, 5-8, 19 and 20 are rejected under 35 U.S.C. 102 (1) (a) as being anticipated by Sekar et al. U.S. Pub. No. 2021/0201359 A1, (hereinafter Sekar).
Regarding claim 1.
Sekar teaches a system integrated with a communication platform for assisting a routing of a communication (Sekar teaches in para. [0228]-[0229] the first process includes applying a machine learning algorithm across the interaction data from the past interactions to identify patterns correlating one or more factors to a desired outcome relevant to a type of customer given a type of interaction…, and further, Sekar teaches in para. [0234] the second process includes receiving information from the contact center to generate the routing recommendation…), comprising:
a processing unit configured to obtain context information indicating a context of the communication, and to determine routing information based on the context information for assisting routing of the communication (Sekar teaches in para. [0234] receiving information from the contact center to generate the routing recommendation. For example, in this case, the second process may include the steps of: a) receiving contact center-side data from the first contact center relating to the first incoming interaction,…, and further, Sekar teaches in para. [0191] the routing process 800 may begin at step 805 where an incoming interaction is identified. The incoming interaction represents a communication between a customer and the contact center system 200 that has been initiated, but not connected. For example, the incoming interaction may be a communication just instigated by a customer (referenced for the example as a “first customer”) over any available communication channel…);
wherein the processing unit comprises a neural network model implemented as a part of a contact center or configured to communicate with the contact center, wherein the neural network model is trained based on data endpoints of the contact center (Sekar teaches in para. [0056] one or more of the included models 252 may be configured to predict customer or agent behavior and/or aspects related to contact center operation and performance…, which are common to complex systems such as those discussed herein. Given the foregoing requirements, a machine learning or neural network-based approach is presently a preferred embodiment for implementing the models 252. Neural networks, for example, may be developed based upon empirical data using advanced regression algorithms and further, Sekar teaches in para. [0054] the analytics module 250, it may be configured to provide systems and methods for performing analytics on data received from a plurality of different data sources as functionality described herein may require. In accordance with example embodiments, the analytics module 250 also may generate, update, train, and modify predictors or models 252 based on collected data, such as, for example, customer data, agent data, and interaction data…), and is configured to provide the routing information to assist the routing of the communication based on the context information (Sekar teaches in para. [0011] the customer-side of the interaction, for example, routing strategies can become more personalized in accordance with specific customer preferences and a present emotional state, thereby making routing more customer centric…, thereby making routing more customer centric. On the contact center-side of the interaction, the present customer profiles also may be used toward improving contact center operations, such as, for example: making call forecasting more context oriented and reliable…, (e.g., by anticipating customer needs to reduce the steps needed to complete an interaction and/or alleviate need for customer to provide information during an interaction); and improving customer communications through greater personalization).
Regarding claim 2.
Sekar teaches wherein the endpoints data comprise device-specific data, user-specific data, application-specific data, service-specific data, third-party specific data, or any combination of two or more of the foregoing (Sekar teaches in para. [0097] the message may be generated automatically by the script processing module based on a message template provided by the script, where portions of the template that contain customer-specific and incident-specific data are automatically filled in based on data collected about the customer (e.g., from the customer profile). Note that here, the claim lists features in the alternative. While the claim lists a number of optional limitations only one limitation from the list is required and needs to be met by the prior art. However, the prior art of record Sekar addressed at least the limitations of “user-specific data, application-specific data, service-specific data”).
Regarding claim 5.
Sekar teaches wherein the routing information comprises a routing suggestion, and wherein the neural network model is configured to generate the routing suggestion for the communication (Sekar teaches in para. [0179] a routing recommendation 775. The routing engine 735 may then transmit the routing recommendation to the contact center system 200 for use in routing the incoming interaction to a particular agent. Also, see para. [0180]-[0191]).
Regarding claim 6.
Sekar teaches wherein the neural network model is trained based on past interactions between customers and agents, wherein the past interactions comprise positive past interactions, negative past interactions, or a combination of both the positive past interactions and the negative past interactions (Sekar teaches in para. [0160] the emotional state may be represented by at least one descriptor representative of either a negative emotional state or a positive emotional state…The interaction data included in the dataset may include data from the interactions evidencing the negative and positive emotional states… Note that here, the claim lists features in the alternative. While the claim lists a number of optional limitations only one limitation from the list is required and needs to be met by the prior art. However, the prior art of record Sekar addressed both of the limitations of “negative and/or positive interaction”).
Regarding claim 7.
Sekar teaches wherein the neural network model is integrated with the communication platform, and is configured to utilize customer data collected over omnichannel communication channels associated with the communication platform to modify process flows for the contact center, automate actions for customers of the contact center, improve communication service for the contact center, or two or more of any of the foregoing (Sekar teaches in para. [0032] receiving orders, or solving problems with products or services already received. Within a contact center, such interactions between contact center agents and outside entities or customers may be conducted over a variety of communication channels, such as, for example, via voice (e.g., telephone calls or voice over IP or VoIP calls), video (e.g., video conferencing), text (e.g., emails and text chat), screen sharing, co-browsing, or the like. Note that here, the claim lists features in the alternative. While the claim lists a number of optional limitations only one limitation from the list is required and needs to be met by the prior art. However, the prior art of record Sekar addressed the limitation of “communication channel”).
Regarding claim 8.
Sekar teaches wherein the system is configured to utilize the neural network model for interactive routing of the communication for matter handling (Sekar teaches in para. [0056] a machine learning or neural network-based approach is presently a preferred embodiment for implementing the models 252. Neural networks, for example, may be developed based upon empirical data using advanced regression algorithms and further, Sekar teaches in para. [0144] as will be discussed more below, this prediction may be used to select an agent that is more adept at handling interactions with frustrated or angry customers).
Regarding claims 19 and 20.
Claims 19 and 20 incorporate substantively all the limitation of claim 1 in method and a computer-product comprising a non-transitory medium form and are rejected under the same rationale. Furthermore, regarding the limitation of a non-transitory storage medium, the prior art of record Sekar teaches in para. [0059].
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Sekar in view of Dutta et al. U.S. Pub. No. 2022/0200934 A1, (hereinafter Dutta).
Regarding claim 3. Sekar teaches the system of claim 1.
Sekar does not explicitly teach wherein the neural network model or another neural network model of the system comprises a bot trained for a specific topic, trained for a specific department, or trained based on knowledge of a specific person.
Dutta teaches wherein the neural network model or another neural network model of the system comprises a bot trained for a specific topic, trained for a specific department, or trained based on knowledge of a specific person (Dutta teaches in para. [0039] one or more artificial neural networks…A machine learning model, such as an artificial neural network, of conversation model 218 may be trained to map utterances of user 110 to intents. Thus, when user 110 makes an utterance, conversation model 218 may determine an intent. Conversation model 218 may then generate a response that corresponds to the determined intent. Thus, the response generated by conversation model 218 may mimic the style of the specific person… Note that here, the claim lists features in the alternative. While the claim lists a number of optional limitations only one limitation from the list is required and needs to be met by the prior art. However, the prior art of record Dutta addressed the limitations of “neural network model or another neural network model trained based on a knowledge of a pesron”).
Therefore, Sekar and Dutta are analogues arts and they are in the same field of endeavor as they both are directed to using one or more artificial neural networks that include a machine learning to train them in a specific knowledge of persons and subjects.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of using one or more artificial neural networks and a machine learning to be trained to map utterances of user to intents ([0039] as taught, by Dutta into the teachings of Sekar invention. One would have been motivated to do so in order to enable the method utilizing a cloud computing as a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. The method enables allowing a cloud consumer to unilaterally provision computing capabilities automatically without requiring human interaction with the service's provider. The method enables allowing cloud computing environment to offer infrastructure, platforms and/or software as services for which the cloud consumer not need to maintain resources on a local computing device, so that capabilities are rapidly and elastically provisioned.
Regarding claim 4.
Sekar teaches wherein the specific person is a sales executive of a company having deal-specific insights gained from years of experience, and wherein the bot is trained based on the deal-specific insights (Sekar teaches in para. [0208] the personal bot 405 of the present invention may collect feedback and survey details whenever provided by customers. The personal bot can understand if a customer is satisfied with a resolution provided by an agent not only by a customer satisfaction score, but also through data driven models trained to automatically infer such feedback from the statements made by the customer at the end of the interaction).
Claims 9-13 are rejected under 35 U.S.C. 103 as being unpatentable over Sekar in view of George et al. U.S. Pub. No. 2024/0378392 A1, (hereinafter George).
Regarding claim 9. Sekar teaches the system of claim 8.
Sekar does not explicitly teach wherein the interactive routing is based on a health score.
However, George teaches wherein the interactive routing is based on a health score (Ronen teaches in para. [0097] wherein the overall intent health score is based on a weighted combination of the calculated scores for the utterance-level health indicators for the intent. At step 425, the method 400 continues by generating a user interface that displays the overall intent health score for a select one of the intents (hereinafter “selected intent”) of the collection of intents for communication to a user).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of the calculated scores for the utterance-level health indicators for the intent ([0097] as taught, by George teaches into the method calculating the overall intent health score for each intent of the collection of intents that ensures that the performance of conversational bots is enhanced effectively.
Regarding claim 10.
George teaches wherein the health score is based on an experience with a specific customer, and wherein the processing unit is configured to cause the communication to be routed to a specific customer support manager based on the health score (George teaches in para. [0097] the generated user interface may further display the calculated scores for the utterance-level health indicators and the intent-level static validation indicator for the select intent that are used to calculate the overall intent health score for the select intent).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of the display the calculated scores for the utterance-level health indicators and the intent-level static validation indicator for the select intent that are used to calculate the overall intent health score for the select intent ([0097] as taught, by George teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the type of dynamic feedback that may allow a user to improve intent health in a highly efficient manner. (George [0097]).
Regarding claim 11.
Sekar does not explicitly teach wherein the health score is matter specific, customer specific, agent specific, organization specific, or any combination of two or more of the foregoing.
However, George teaches wherein the health score is matter specific, customer specific, agent specific, organization specific, or any combination of two or more of the foregoing (George teaches in para. [0091] wherein the overall intent health score is based on a weighted combination of the calculated scores for the utterance-level health indicators for the intent. At step 425, the method 400 continues by generating a user interface that displays the overall intent health score for a select one of the intents (hereinafter “selected intent”) of the collection of intents for communication to a user, and George further teaches in para. [0056]-[0057] user interface provided to the bot author may dynamically update health results per changes made by the user to the collection of intents and associated utterances… Intent Health may be regarded as an indicator of the overall health of an intent. Different labels may be used to describe the health of an intent, such as, “Good” or “Ok”, or “Poor”. These labels may be derived by mapping intent health scores (e.g., out of 100) to specific thresholds…).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of using the bot author may dynamically update health results per changes made by the user to the collection of intents ([0056]-[0057]) as taught, by George teaches into the teachings of Sekar invention. One would have been motivated to do so in order to an iterative process until the bot author deems that the NLU domain is in good health. Then the bot can be trained and deployed to serve customer requests. (George. [0056]).
Regarding claim 12.
Sekar does not explicitly teach wherein the health score is an overall score regarding the communication, regarding a specific agent, or regarding the communication platform providing the communication.
However, George teaches wherein the health score is an overall score regarding the communication, regarding a specific agent, or regarding the communication platform providing the communication (George teaches in claim 9 and para. [0097] the step of generating a user interface that displays the overall intent health score for a select intent of the collection of intents for communication to a user and the method may further include the steps of dynamically updating the user interface by recalculating the overall intent health score for the select intent for communication to the user and the included sub-scores related to the indicators.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of the display the calculated scores for the utterance-level health indicators and the intent-level static validation indicator for the select intent that are used to calculate the overall intent health score for the select intent ([0097] as taught, by George teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the type of dynamic feedback that may allow a user to improve intent health in a highly efficient manner. (George [0097]).
Regarding claim 13.
Sekar does not explicitly teach wherein the communication platform is configured to assist matter handling for one or more customers, and wherein the health score is a real-time or near real-time evaluation of performance of the communication platform.
However, George teaches wherein the communication platform is configured to assist matter handling for one or more customers, and wherein the health score is a real-time or near real-time evaluation of performance of the communication platform (George teaches in para. [0046] the terms “interaction” and “communication” are used interchangeably, and generally refer to any real-time and non-real-time interaction that uses any communication channel including, without limitation, telephone calls (PSTN or VOIP calls), emails, vmails, video, chat, screen-sharing, text messages, social media messages, WebRTC calls, etc…Intent Health and Conversational Bots).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of a real-time and non-real-time interaction that uses any communication channel ([0046] as taught, by George teaches into the teachings of Sekar invention. One would have been motivated to do so since this method allows users to quickly identify and highlight potential issues that might cause performance degradation of an NLU model. (George [0049]).
Claims 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Sekar in view of Adibi et al. U.S. Pub. No. 2025/0037137 A1, (hereinafter Adibi).
Regarding claim 14. Sekar teaches the system of claim 1.
Sekar does not explicitly teach wherein the neural network model is trained based on a skillset of an agent.
However, Adibi teaches wherein the neural network model is trained based on a skillset of an agent (Adibi teaches in para. [0060] a customer may ask for the same agent as before. A customer may ask for a specific agent... A customer may ask for any combination of filters such as name, last name, skill set, etc.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of customer may ask for a specific agent based on skill set ([0060] as taught, by Adibi teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the system executes an agent picker functionality within an automation infrastructure that performs operations comprising receiving a communication from a customer, immediately analyzing the communication to determine the right agent, thus automatically understanding the state of the room parsing a knowledgebase for some of the conversation to the subject associated with the customer's communication and providing the state to agent within a unified interface during the communication with customer and capability to rate other party and add and drop multimedia to all containers.
Regarding claim 15.
Adibi teaches wherein the agent comprises an Unified Communication (UC) agent, a Contact Center (CC) agent, a Communication Platform as a Service (CPaaS) agent, or any of other cloud-based platform agents (Adibi teaches in para. [0002]-[0003] contact center provides a toll free number and might provide all these channels to their customers and terms such as multi-channel or omni-channel are used to represent such capability and further, Adibi teaches in para. [0005] providing the state of the room to agent within a unified interface during the communication with the customer, capability to rate other party and add and drop multimedia to all containers).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of providing the state of the room to agent within a unified interface during the communication with the customer ([0005] as taught, by Adibi teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the system executes an agent picker functionality within an automation infrastructure that performs operations comprising receiving a communication from a customer, immediately analyzing the communication to determine the right agent, thus automatically understanding the state of the room parsing a knowledgebase for some of the conversation to the subject associated with the customer's communication and providing the state to agent within a unified interface during the communication with customer and capability to rate other party and add and drop multimedia to all containers.
Claims 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Sekar in view of Hamid et al. U.S. Pub. No. 2025/0217371 A1, (hereinafter Adibi).
Regarding claim 16. Sekar teaches the system of claim 1.
Sekar does not explicitly teach wherein the processing unit is configured to provide a response to a customer as a part of the communication, and wherein the processing unit is also configured to provide a confidence score that the response is accurate, a source attribution for the response, a confidence score that the response satisfies a customer inquiry, a confidence score that response is complete, a likelihood of a follow-up request associated with the response, a validation of the response, or two or more of any combination of the foregoing.
However, Hamid teaches wherein the processing unit is configured to provide a response to a customer as a part of the communication, and wherein the processing unit is also configured to provide a confidence score that the response is accurate, a source attribution for the response, a confidence score that the response satisfies a customer inquiry, a confidence score that response is complete, a likelihood of a follow-up request associated with the response, a validation of the response, or two or more of any combination of the foregoing (Hamid teaches in para. [0014] performing a third search of the user contact content store, using the search feature set, to identify a candidate user contact, and providing, as input to a response confidence analysis model that is configured to predict a responsiveness of results from the first search, the second search, and the third search to the natural language input results from the first search and a first intent confidence score associated with the first request classifier, results from the second search and a second intent confidence score associated with the second request classifier, and results from the third search and a third intent confidence score associated with the third request classifier…, and further, Hamid teaches in para. [0043]-[0045 and [0051]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of providing, as input to a response confidence analysis model that is configured to predict a responsiveness of results from the first search, the second search, and the third search to the natural language input results from the first search and a first intent confidence score associated with the first request classifier ([0014] as taught, by Hamid teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the method can provide specialized or curated responses that are tailored to be relevant and actionable based on the user's natural language input.
Regarding claim 17. Sekar teaches the system of claim 1.
Sekar does not explicitly teach wherein the routing information comprises a suggested routing to an agent, and wherein the processing unit is configured to provide a confidence scoring for the suggested routing to the agent.
However, Hamid teaches wherein the routing information comprises a suggested routing to an agent, and wherein the processing unit is configured to provide a confidence scoring for the suggested routing to the agent (Hamid teaches in para. [0326] generative content service then analyzes the results (using the intent confidence scores for each of the request types/content stores) to rank and/or filter the results…, and further, Hamid teaches in para. [0328] selecting an intake category may cause the portal to route a user to different features of the help desk…).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of generative content service then analyzes and selecting an intake category may cause the portal to route a user to different features ([0326] and [0328]) as taught, by Hamid teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the method can provide specialized or curated responses that are tailored to be relevant and actionable based on the user's natural language input.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Sekar in view of Feast U.S. Pub. No. 2019/0158671 A1, (hereinafter Feast).
Regarding claim 18. Sekar teaches the system of claim 1.
Sekar does not explicitly teach wherein the system also comprises a user interface generator configured to provide a user interface, the user interface configured to present the routing information to a user, wherein the user interface is configured to receive a user input to influence the routing of the communication to an agent.
However, Feast teaches wherein the system also comprises a user interface generator configured to provide a user interface, the user interface configured to present the routing information to a user, wherein the user interface is configured to receive a user input to influence the routing of the communication to an agent (Feast teaches in para. [0044] routing engine 160 may then route the request to the automate response chat bot technology 130 based on the requestor selection, where to begin interacting with the requestor. As the requestor enters more information about themselves and their goal(s) in a chat session, a text analytics component may be used to parse the inputs typed by a requestor…).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the
claimed invention to modify the teachings of using routing engine 160 may then route the request to the automate response chat bot technology 130 based on the requestor selection ([0044]) as taught, by Feast teaches into the teachings of Sekar invention. One would have been motivated to do so in order to the method enables concerning a call center cost effectively for providing an excellent customer service by answering questions or providing relevant information to callers quickly and politely in an efficient manner.
Conclusion
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/BERHANU SHITAYEWOLDETSADIK/Primary Examiner, Art Unit 2455
