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 .
This Office Action is in response to the submission filed October 23, 2024. Xlaims1-20 are pending.
Claim Rejections - 35 USC § 101
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is directed to a system for generating response to a received input. Claim recites limitations for:
receiving an input from a user is data gathering step that can be achieved by a person hearing an utterance;
determining an intent of the input can achieved by the person mentally recognizing the words of the utterance and mentally understanding the request/question of the utterance;
based on the intent, determining a response from a pre-generated set of responses can be achieved by the person, once the intent is understood, selecting an appropriate response from a list of prepared responses; and
outputting the response to the user can be achieved by the person speaking or presenting the appropriate response using pen and paper.
The recited limitations are directed a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of the generic computer devices and processor. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the recited generic computer devices and processor amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The claims are not patent eligible.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as indicated with respect to integration of the abstract idea into a practical application, the additional elements of the generic computer devices and processor to perform the various steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
Dependent claims 2-16 do not integrate the judicial exception into a practical application and do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations of the dependent claims are directed to steps of organizing or manipulating data for generating intents and responses; utilizing rules and principles of natural language processing (including mathematical algorithms for implementing learning models) to generate intents and responses; recognizing and understanding utterances; performing mathematical algorithms for similarity processing; data gathering steps for receiving data; selecting response and extra-solution activities for transmitting/presenting output.
Claim 17 is directed to a response generation system for generating a pre-generated set of responses. Claim 17 recites limitations for:
determining a set of potential input phrases can be achieved by a person making a list of possible questions/request that they can expect to be asked given a context or situation;
determining, optionally using a large language model, a set of responses based on the potential input phrases can be achieved by the person using rules and principles of natural language processing, creating a list of responses for the list of questions/requests; and
transmitting one or more responses of this set of responses to a first computer device can be achieved by the person listing the responses on paper and presenting/providing the list to another person.
The recited limitations are directed a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of the generic computer devices and processor. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the recited generic computer devices and processor amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The claims are not patent eligible.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as indicated with respect to integration of the abstract idea into a practical application, the additional elements of the generic computer devices and processor to perform the various steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
Dependent claims 18-19 do not integrate the judicial exception into a practical application and do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations of the dependent claims are directed to determining responses based on a desired context/content/situation; and steps for data gathering utilizing generic computer components to receive inputs and adding the received inputs to the list.
Claim 20 is directed to a method of generating a response to an input. Claim 20 recites limitations for:
identifying a pre-generated set of responses can be achieved by the person using rules and principles of natural language processing, creating a list of responses to a set questions/requests;
receiving an input from a user is data gathering step that can be achieved by a person hearing an utterance;
determining an intent of the input can achieved by the person mentally recognizing the words of the utterance and mentally understanding the request/question of the utterance;
based on the intent, determining a response from the pre-generated set of responses can be achieved by the person, once the intent is understood, selecting an appropriate response from the list of prepared responses;
and outputting the response to the user can be achieved by the person speaking or presenting the appropriate response using pen and paper;
optionally, wherein the pre-generated set of responses is generated before the receipt of the input, preferably at least an hour before, a day before, and/or a week before, the receipt of the input, is a step for organizing and manipulating data where the person can generate the response list in advance.
The recited limitations are directed a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of the generic computer and implied generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the recited generic computer and implied generic computer components amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea. The claims are not patent eligible.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as indicated with respect to integration of the abstract idea into a practical application, the additional elements of the generic computer and implied generic computer components to perform the various steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
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 –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Bhowal et al (US Patent Application Publication No. 2020/0327197), hereinafter Bhowal.
Bhowal discloses a document based response generation system. Regarding claim 1, Bhowal teaches an automated response system [figures 1-9] for generating a response to a user input, the system comprising a first computer device [user device 116] , the first computer device comprising a processor [118] for: receiving an input from a user [user provided utterance 136; para 0043-0044] ; determining an intent of the input [intent 138; para 0043]; based on the intent, determining a response from a pre-generated set of responses [predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; 0045-0048 -- response based on predefined answers]; and outputting the response to the user [response 204/142; response sent to user device for display or presentation].
Regarding claim 2, Bhowal teaches the system of claim 1, wherein the processor and/or a processor of a second computer device [computing device 102] is arranged to generate the pre-generated set of responses [predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; ] by providing a set of potential input phrases [set of generated utterances 126/set of variation utterances 134] to a machine learning model [para 0042 –machine learning to anticipate what questions may be asked].
Regarding claim 3,Bhowal teaches the system of claim 2, wherein the processor is arranged to identify the set of potential input phrases [para 0042 –machine learning to anticipate what questions may be asked].
Regarding claim 4, Bhowal teaches the system of claim 3, wherein the first computer device comprises a communication interface that is arranged to receive each of the pre-generated set of responses and the set of potential input phrases from a second computer device [communications interface 114].
Regarding claim 5, Bhowal teaches the system of claim 3, wherein the processor is arranged to determine the intent of the input by determining a similarity between the input and one or more potential input phrases from the set of potential input phrases [para 0045-0047 -- The response generation component 128 calculates a distance between the user-provided utterance 136 and each utterance filtered from the set of generated utterances 126. The response generation component 128 assigns a similarity score to each filtered utterance from the set of generated utterances 126 based on the computed distance for each utterance].
Regarding claim 6, Bhowal teaches the system of claim 3, wherein the processor is arranged to: determine that a similarity between the input and a most similar potential input phrase of the set of potential input phrases is beneath a threshold value; and based on the determination, transmit the input to a second computer device [para 0045-0046 – smaller distance value].
Regarding claim 7, Bhowal teaches the system of claim 1, wherein the first computer device comprises a communication interface for receiving the pre-generated set of responses from a second computer device [communications interface 114].
Regarding claim 8, Bhowal teaches the system of claim 1, wherein the processor is arranged to convert the input to a query and determine an intent of the query, optionally using a machine learning model [para 0043-0044 –user-provided query; para 0061 – model outputs most probable intent].
Regarding claim 9, Bhowal teaches the system of claim 1, wherein the system comprises a second computer device, the second computer device being arranged to generate the pre-generated set of responses prior to the receiving of the input [predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; ], optionally using a machine learning model [para 0042 –machine learning to anticipate what questions may be asked].
Regarding claim 10, Bhowal teaches the system of claim 9, wherein the second computer device is arranged to transmit the pre-generated set of responses to the first computer device prior to the receiving of the input [para 0054 – database 312 stored remotely].
Regarding claim 11, Bhowal teaches the method of claim 9, wherein the first computer device comprises a communication interface [communications interface 114], the communication interface being arranged to: transmit the input and/or the intent to the second computer device [para 0044], and receive a response from the second computer device, the response being selected by the second computer device from among the pre-generated set of responses [response 204/142; response sent to user device for display or presentation].
Regarding claim 12, Bhowal teaches . The system of claim 9, wherein the second computer device comprises: a more powerful processor than the first computer device, preferably a more powerful GPU; and/or a server with access to a high-end large language model [para 0024].
Regarding claim 13, Bhowal teaches the system of claim 1, wherein the processor is arranged to: determine that the pre-generated set of responses does not contain a suitable response [para 0050 – response unsatisfactory or failure]; and in response to the determination: provide a default response [para 0077 – feedback request]; and/or. transmit, to a second computer device, the input, a query determined from the input and/or the intent; and receive a response from the second computer device.
Regarding claim 14, Bhowal teaches the system of claim 1, wherein the processor is arranged to: determine, based on the set of pre-generated responses, a set of available responses; and determine the response from this set of available responses; wherein: the set of available responses is dependent on one or more of: a state of the user; a history of previous actions of the user; and/or a history of inputs from the user [para 0080 – updates for responses based on user feedback]; and/or the set of available responses is determined so as to avoid repetition of a response; and/or the set of available responses is determined so as to encourage the user to follow a predetermined conversation path.
Regarding claim 15, Bhowal teaches the system of claim 1, wherein the processor is arranged to determine one or more characteristics of the input [para 0060-0071 – analysis by pre-trained NLU machine learning model using distance calculations], and determine the intent and/or the response based on the characteristics [para 0060-0071 – analysis by pre-trained NLU machine learning model using distance calculations].
Regarding claim 16, Bhowal teaches the system of claim 1, wherein the processor is arranged to determine a persona for the response [para 0042 – document information], and to determine the response based on the persona [para 0042 -- response generation component applies machine learning (pattern recognition) to anticipate what questions may be asked by users based on information/facts in the policy document. The response generation component generates all possible questions (utterances) which may be asked by users and maps those questions to answers extracted from the document. The system converts this information into the set of generated utterances and answers for use by the chatbot system 100].
Regarding claim 17, Bhowal teaches a response generation system [Figures 1-9] for generating a pre-generated set of responses for an automated response system, the system comprising a second computer device [computing device 102], the second computer device comprising a processor [106] for: determining a set of potential input phrases [set of generated utterances 126/set of variation utterances 134]; determining, optionally using a large language model, a set of responses based on the potential input phrases [predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; para 0042 -- by users based on information/facts in the policy document. The response generation component generates all possible questions (utterances) which may be asked by users and maps those questions to answers extracted from the document. The system converts this information into the set of generated utterances and answers for use by the chatbot system 100]; and transmitting one or more responses of this set of responses to a first computer device [response 204/142; response sent to user device for display or presentation].
Regarding claim 18, Bhowal teaches the system of claim 17, wherein the processor is arranged to determine a persona for the response [para 0042 – document information], and to determine the response based on the persona [para 0042 -- response generation component applies machine learning (pattern recognition) to anticipate what questions may be asked by users based on information/facts in the policy document. The response generation component generates all possible questions (utterances) which may be asked by users and maps those questions to answers extracted from the document. The system converts this information into the set of generated utterances and answers for use by the chatbot system 100].
Regarding claim 19, Bhowal teaches the system of claim 17, wherein the second computer device comprises a communication interface for receiving one or more supplementary input phrases from a first computer device [para 0077 – feedback request]; and including these supplementary input phrases in the set of potential input phrases [para 0080 – updates for responses based on user feedback].
Regarding claim 20, Bhowal teaches a computer-implemented method [figures 1-9] of generating a response to an input, the method comprising: identifying a pre-generated set of responses[predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; 0045-0048 -- response based on predefined answers]; receiving an input from a user [user provided utterance 136; para 0043-0044]; determining an intent of the input; based on the intent [intent 138; para 0036; 0043], determining a response from the pre-generated set of responses [predefined answers 132; para 0034 -- The set of generated utterances 126 includes predefined answers 132 corresponding with the set of generated utterances. Each utterance in the set of generated utterances is mapped to at least one corresponding answer/response in the predefined answers 132. An answer includes the information requested in an utterance; 0045-0048 -- response based on predefined answers]; and outputting the response to the user [response 204/142; response sent to user device for display or presentation]; optionally, wherein the pre-generated set of responses is generated before the receipt of the input, preferably at least an hour before, a day before, and/or a week before, the receipt of the input [para 0042].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Trehan (US Patent Application Publication No. 2021/0350073) teaches generating input intent maps associated with user input; matching the set of input maps with a set of pre-stored sets of intent maps; determining distance of set of input intent maps relative to set of pre-stored sets of intent maps; and providing a predetermined response mapped to pre-stored sets of intent maps to the user.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANGELA A ARMSTRONG whose telephone number is (571)272-7598. The examiner can normally be reached M,T,TH,F 11:30-8:00.
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ANGELA A. ARMSTRONG
Primary Examiner
Art Unit 2659
/ANGELA A ARMSTRONG/Primary Examiner, Art Unit 2659
Prosecution Insights