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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4/7/2026 has been entered.
Claims Status
Claims 2-6, 8-13 and 15 have been cancelled.
Claims 16-24 are newly added.
Claims 1, 7, 14, and 16-24 are pending.
Claim 7 is withdrawn as set forth previously.
Claims 21-24 are hereby withdrawn through election by original presentation.
Claims 1, 14 and 16-20 stand rejected.
Objection - Title
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. The following title is suggested:
Device, method and storage medium for determining unclear item information through automated processing
Objection – Claims
Claim 1 is objected to because it omits punctuation at the end of the following limitation. The Examiner believes a semicolon should be added as indicated at [?]:
second obtaining code configured to cause at least one of the at least one processor to obtain a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value [?].
Appropriate correction is required.
Claim 14 is objected to because of grammatical errors. Claim 14 recites identifying the item information as unclear based on the first determination result and the second determination result do not match each other. The claim should be reworded as either:
based on a determination that the first determination result and the second determination result do not match each other, or,
based on the first determination result and the second determination result failing to
Appropriate correction is required.
Election by Original Presentation
Newly submitted claims 21-24 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
Group I: Claims 1, 14, and 16-20 (classified in G06Q 30/0603)
Group II: Claims 21-24 (classified in G06V 10/70).
The inventions are independent or distinct, each from the other because:
Groups I and II are directed to related inventions that, as claimed, have a materially different design, mode of operation, function, or effect and are mutually exclusive.
In the instant case, group I requires first calculating code configured to cause at least one of the at least one processor to input the character string into a natural language processing model (NLP), and, summarization code configured to cause at least one of the at least one processor to input the character string into a pre-trained machine learning model to generate a summary. Such features are note required by group II.
In the other hand, group II requires at least certain features that are not required by group I. For example, group II requires first calculating code configured to cause at least one of the at least one processor to input the image into a machine learning model configured to solve a classification task, and, processing code configured to cause at least one of the at least one processor to input the image into a Convolutional Neural Network (CNN) model to generate a processed image, the CNN model configured to generate an activation map or saliency map associated with a region on the image, and to extract the processed image based on the map. Such features are not required by group I.
Furthermore, there is nothing of record to show them to be obvious variants.
Per MPEP 819, the general policy of the Office is that applicants are not permitted to shift to claim another invention after an election is made and an Office action on the merits is made on the elected invention. Specifically, the applicant may not disaffirm or change their election, as a matter of right, after making an oral election and receiving an Office action based upon that oral election in a pending application. See 37 CFR 1.142(b). In addition, the applicant cannot, as a matter of right, file a request for continued examination (RCE) on claims that are independent and distinct from the claims previously claimed and examined (i.e., applicant cannot switch inventions by way of an RCE as a matter of right). See MPEP § 706.07(h), subsection VI.(B). When claims are presented which the examiner finds are drawn to an invention other than the one elected, he or she should treat the claims as outlined in MPEP § 821.03.
A search or examination burden exists in view of the shift because the inventions have acquired a separate status in the art in view of their different classification. Further, there is a search and/or examination burden for the patentably distinct inventions because the inventions have acquired a separate status in the art due to their recognized divergent and materially distinct subject matters, which require unique considerations with respect to the applicable prior art as well as requiring uniquely different fields of search (e.g. for employing different search queries, consulting searching different classes/subclasses).
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits.
Accordingly, claims 21-24 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
Response to Arguments
I. Applicant’s arguments made with respect to the rejection under 35 USC 101 have been fully considered but are not persuasive.
The Examiner initially reiterates that, in view of the emphasized limitations below, the claims continue to recite an abstract idea because they set forth or describe either ‘certain methods of organizing human activity’ or ‘mental processes’. In Prong One examiners evaluate whether the claim recites a judicial exception, i.e. whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. The presence of additional elements for consideration does not negate the recitation of the abstract idea.
Turning to Prong Two of Step 2A, Applicant argues that the “dual-path architecture produces a technical result that enables automated detection of unclear information by identifying internal inconsistencies within a single piece of item information, which is a capability that did not previously exist and could not be replicated by human mental processes”. Initially, the Examiner notes that the court has indicated that mere automation of manual processes are not sufficient to show an improvement in computer functionality. That is, automating analysis for “detection of unclear information by identifying internal inconsistencies within a single piece of item information” is mere automation through generic computing components.
Merely using machine learning models, NLP models, or the like does not go beyond mere instructions to perform the method on a generic component or machinery. Moreover, leveraging existing NLP or machine learning technology at a high level due to their improved efficiency is not tantamount to a technical improvement. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. See MPEP 2106.05(f)(2).
Furthermore, the result – “automated unclear information detection” – is not a technical result as alleged by applicant. This improves the abstract idea of detecting unclear information, and relies upon the speed and efficiency of generic computing components. The claimed invention does not improve the functioning of the computer itself or any underlying technology or technical field.
With respect to McRO, the Examiner holds that a comparison to the circumstances and concepts described in McRO is inapposite. If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. If the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology (MPEP 2106.05(a))
Unlike McRO, the specification and claims set forth only at a high level of generality the use machine learning models, an NLP model, and computers and “code”. Neither claims nor the specification provide any detail concerning the technical explanation of how the underlying technical processes are performed and lack any restriction on the manner in which these steps are performed by the computer, other than their invocation of the generic computing components. Applicant’s assertion is little more than a bare assertion without the necessary detail to demonstrate the alleged improvement. Furthermore, a recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it” (see MPEP 216.05(f)).
While Applicant alleges that the “pre-trained machine learning model” and “NLP model” are not generic processors, they are described as “known” in at least 0048, 0068 and 0070, for example:
0048: The item 17 may be classified based on item information using a known machine learning model 36a. For example, the result of classification (index 71) may be obtained by inputting a character string to a convolutional neural network (CNN) or bidirectional encoder representations from transformers (BERT) for natural language processing (NLP) and solving a classification task.
0068: For instance, a known machine learning model 36h (e.g., CNN, FastText, Doc2Vec, Sentence2Vec, Data2Vec, or BERT) may be used to encode a character string. When receiving a character string, the machine learning model 36h outputs a distributed representation of the character string. Encoded data (e.g., distributed representation) is an example of the index 71. An image may be encoded using a known machine learning model 36i (e.g., CNN).
0070: “A character can be extracted using a known machine learning model 36m for optical character recognition (OCR)”
Moreover, there is nothing in the specification that indicates the machine learning models or the NLP model are beyond generic models. They are described only at a high level of generality in terms of their use in facilitating the abstract idea, and offer minimal restriction on the underlying technical operations they perform. Accordingly, the Examiner maintained that the additional elements fail to integrate the recited exception into a practical application.
Turning lastly to Step 2B, the Examiner again disagrees. The Examiner acknowledges the citation to Paragraph 0092. Similar to the above discussion under Prong Two, allowing a device to determine whether item information is unclear through automated processing does not add significantly more. This is again because the claims merely leverage generic computer components as a mere tool to implemented the abstract idea. Although the claims leverage multiple computing components, there is nothing of record that (i) an unconventional arrangement of these components exists and, even presuming arguendo the arrangement is “unconventional” (which the Examiner does not acquiesce), the unconventional arrangement results in an improvement to the abstract idea itself rather than the functioning of the computer or another technology or technical field.
Taken individual or as a whole, the claims do not offer an unconventional arrangement leading to a technical improvement, nor do they otherwise provide “significantly more”. Accordingly the rejection under 35 USC 101 has been maintained.
II. Applicant’s arguments made with respect to the rejection under 35 USC 103 have been fully considered and are persuasive. For further discussion see below under the heading Subject Matter Allowable Over the Prior Art.
Claim Rejections - 35 USC § 101 – Judicial Exception
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, 14 and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Regarding claims 1, 14 and 16-20, under Step 2A claims 1, 14 and 16-20 recite a judicial exception (abstract idea) that is not integrated into a practical application and does not provide significantly more.
Under Step 2A (prong 1), and taking claim 1 as representative, claim 1 recites an information processing apparatus used to:
calculate a first probability that the one of the items corresponds to a certain category;
obtain a first determination result, which determines that the one of the items corresponds to the certain category when the first probability is greater than or equal to a predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the first probability is less than the predetermined threshold value;
generate a summary;
calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
obtain a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value
execute a comparison process that compares the first determination result with the second determination result; and
identify the item information as unclear based on the first determination result and the second determination result.
These limitations recite ‘certain methods of organizing human activity’, such as by performing commercial interactions (see: MPEP 2106.04(a)(2)(II)). This is because claim 1 sets forth or describes obtaining indices used to compare item information. This represents the performance of marketing or sales activities or behaviors, which are commercial interactions and fall under organizing human activity. Accordingly, claim 1 recites an abstract idea because claim 1 recites limitations that fall within the “Certain methods of organizing human activity” grouping of abstract ideas.
Additionally, claim 1 can also be understood to recite limitations that set forth or describe “mental processes” that are performable in the human mind, or by pen and paper. This is because the following operations of claim 1 can be accomplished in the human mind, or using a physical aid such as pen and paper, and represent observations, evaluations or judgments (see: MPEP 2106.04(a)(2)(III)):
calculate a first probability that the one of the items corresponds to a certain category;
obtain a first determination result, which determines that the one of the items corresponds to the certain category when the first probability is greater than or equal to a predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the first probability is less than the predetermined threshold value;
generate a summary;
calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
obtain a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value
execute a comparison process that compares the first determination result with the second determination result; and
identify the item information as unclear based on the first determination result and the second determination result.
Notably, the courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer.
The Examiner also asserts that the high-level data analysis is similar to that held to be an abstract mental process in Electric Power Group (discussed previously). Accordingly, under step 2A (prong 1) claim 1 also recites an abstract idea because claim 1 recites limitations that fall within the “Mental processes” grouping of abstract ideas.
Under Step 2A (prong 2), the abstract idea is not integrated into a practical application. The Examiner acknowledges that representative claim 1 does recite additional elements, including:
at least one of one or more memories configured to store item data related to items registered in an online platform, wherein the item data includes data sets, the data sets each include data fields registered for one of the items, the data fields each include a character string that indicates item information related to the one of the items;
at least one of one or more memories configured to store program code; and
at least one processor configured to operate as instructed by the program code, the program code including:
first calculating code configured to cause at least one of the at least one processor to input the character string into a natural language processing model (NLP),
first obtaining code configured to cause at least one of the at least one processor,
summarization code configured to cause at least one of the at least one processor to input the character string into a pre-trained machine learning model,
second calculating code configured to cause at least one of the at least one processor to input the summary into the NLP model,
second obtaining code configured to cause at least one of the at least one processor to,
comparison code configured to cause at least one of the at least one processor to, and,
identification code configured to cause at least one of the at least one processor to.
Although reciting these additional elements, taken alone or in combination these elements are not sufficient to integrate the abstract idea into a practical application. This is because the additional elements of claim 1 are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Notably, Applicant’s specification refers to “known” machine learning models in 0048, 0068, and 0070.
Furthermore, the courts have emphasized that mere automation of manual processes is not sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)). Lastly, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
In addition to the above, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In view of the above, under Step 2A (prong 2), claim 1 does not integrate the recited exception into a practical application.
Under Step 2B, examiners should evaluate additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Returning to representative claim 1, taken individually or as a whole the additional elements of claim 1 do not provide an inventive concept (i.e. they do not amount to “significantly more” than the exception itself). As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Furthermore, the additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claim 1 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network,
storing or retrieving information from memory,
electronic recordkeeping.
Furthermore, the courts have emphasized that mere automation of manual processes is not sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)).
Even considered as an ordered combination (as a whole), the additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, representative claim 1 does not provide an inventive concept (“significantly more”) under Step 2B, and is therefore ineligible for patenting.
Regarding dependent claims 16-20, dependent claims 16-20 recite more complexities descriptive of the abstract idea itself. For example, claims 16-20 recite further details of the commercial process and/or further mental processes. As such, claims 16-20 are understood to recite an abstract idea under step 2A (prong 1) as discussed above, and because they at least inherit the abstract idea of claim 1.
Under prong 2 of step 2A, the additional elements of dependent claims 16-20 also do not integrate the abstract idea into a practical application, considered both individually or as a whole. More specifically, claims 16-20 rely upon at least similar additional elements as discussed with respect to claim 1. Further additional elements such as using a CNN (claims 16-17), where the pre-trained model is trained (claim 19), and a storing code that causes the processor to store an identification result (claim 20) are also recited only at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea, on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Notably, Applicant’s specification refers to “known” machine learning models in 0048, 0068, and 0070.
Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
Lastly, under step 2B, claims 16-20 also fail to result in “significantly more” than the abstract idea under step 2B. This is again because the claims merely apply the exception on generic computing hardware, generally link the exception to a technological environment, and append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Even when viewed as an ordered combination (as a whole), the additional elements of the dependent claims do not add anything further than when they are considered individually.
In view of the above, claims 16-20 do not provide an inventive concept (“significantly more”) under Step 2B, and are therefore ineligible for patenting.
Regarding claim 14, and under Step 2A (prong 1), claim 14 recites a method to:
obtaining item data related to items registered in an online platform, the item data including data sets, the data sets each including data fields registered for one of the items, and the data fields each including a character string that indicates item information related to the one of the items;
obtaining a first index associated with the one of the items based on one piece of item information;
calculate a first probability that the one of the items corresponds to a certain category;
obtaining a first determination result, which determines that the one of the items corresponds to the certain category when the first probability is greater than or equal to a predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the first probability is less than the predetermined threshold value;
generating processed information by processing the one piece of item information;
generate a summary;
calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
obtaining a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value;
executing a comparison process that compares the first determination result with the second determination result; and
identifying the item information as unclear based on the first determination result and the second determination result do not match each other.
These limitations recite ‘certain methods of organizing human activity’, such as by performing commercial interactions (see: MPEP 2106.04(a)(2)(II)). This is because claim 1 sets forth or describes obtaining indices used to compare item information. This represents the performance of marketing or sales activities or behaviors, which are commercial interactions and fall under organizing human activity. Accordingly, claim 1 recites an abstract idea because claim 1 recites limitations that fall within the “Certain methods of organizing human activity” grouping of abstract ideas.
Additionally, claim 1 can also be understood to recite limitations that set forth or describe “mental processes” that are performable in the human mind, or by pen and paper. This is because the following operations of claim 1 can be accomplished in the human mind, or using a physical aid such as pen and paper, and represent observations, evaluations or judgments (see: MPEP 2106.04(a)(2)(III)):
obtaining a first index associated with the one of the items based on one piece of item information;
calculate a first probability that the one of the items corresponds to a certain category;
obtaining a first determination result, which determines that the one of the items corresponds to the certain category when the first probability is greater than or equal to a predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the first probability is less than the predetermined threshold value;
generating processed information by processing the one piece of item information;
generate a summary;
calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
obtaining a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value;
executing a comparison process that compares the first determination result with the second determination result; and
identifying the item information as unclear based on the first determination result and the second determination result do not match each other.
Notably, the courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer.
The Examiner also asserts that the high-level data analysis is similar to that held to be an abstract mental process in Electric Power Group (discussed previously). Accordingly, under step 2A (prong 1) claim 1 also recites an abstract idea because claim 14 recites limitations that fall within the “Mental processes” grouping of abstract ideas.
Under Step 2A (prong 2), the abstract idea is not integrated into a practical application. The Examiner acknowledges that representative claim 14 does recite additional elements, including:
an information processing device,
an online platform,
inputting the character string into a natural language processing model (NLP),
inputting the character string into a pre-trained machine learning model,
inputting the summary into the NLP model.
Although reciting these additional elements, taken alone or in combination these elements are not sufficient to integrate the abstract idea into a practical application. This is because the additional elements of claim 14 are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Notably, Applicant’s specification refers to “known” machine learning models in 0048, 0068, and 0070.
Furthermore, the courts have emphasized that mere automation of manual processes is not sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)). Lastly, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
In addition to the above, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In view of the above, under Step 2A (prong 2), claim 1 does not integrate the recited exception into a practical application.
Under Step 2B, examiners should evaluate additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Returning to representative claim 14, taken individually or as a whole the additional elements of claim 1 do not provide an inventive concept (i.e. they do not amount to “significantly more” than the exception itself). As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Furthermore, the additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claim 14 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network,
storing or retrieving information from memory,
electronic recordkeeping.
Furthermore, the courts have emphasized that mere automation of manual processes is not sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)). Even considered as an ordered combination (as a whole), the additional elements of claim 14 do not add anything further than when they are considered individually.
In view of the above, representative claim 14 does not provide an inventive concept (“significantly more”) under Step 2B, and is therefore ineligible for patenting.
Subject Matter Allowable Over the Prior Art
Claims 1, 14, and 16-20 remain rejected on other grounds but are allowable over the prior art. Upon review of the evidence at hand, it is hereby concluded that the totality of the evidence, alone or in combination, neither anticipates, reasonably teaches, nor renders obvious the below noted features of applicant’s invention. The allowable features are as follows:
Regarding Claim 1:
summarization code configured to cause at least one of the at least one processor to input the character string into a pre-trained machine learning model to generate a summary;
second calculating code configured to cause at least one of the at least one processor to input the summary into the NLP model to calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
second obtaining code configured to cause at least one of the at least one processor to obtain a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value.
Similarly, claim 14 recites:
generating processed information by processing the one piece of item information; and inputting the character string into a pre-trained machine learning model to generate a summary;
inputting the summary into the NLP model to calculate a second probability indicating a probability that the one of the items corresponds to the certain category;
obtaining a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value.
As amended, claims 1 and 14 each recite a defined chain of interrelated operations in which (1) the character string is input into an NLP model to calculate a first probability, (2) the same character string is input into a pre-trained machine learning model to generate a summary, and (3) the summary is input into the NLP model to calculate a second probability. This leads specifically to obtaining a second determination result, which determines that the one of the items corresponds to the certain category when the second probability is greater than or equal to the predetermined threshold value, and determines that the one of the items does not corresponds to the certain category when the second probability is less than the predetermined threshold value, which culminates in identifying that item information is unclear based upon a comparison of the second determination result and first determination result.
As argued by Applicant, “Feature extraction is structurally different from generating a summary: feature extraction identifies individual linguistic features within the text, whereas summarization generates a condensed representation of the text as a whole.”. The Examiner agrees, and agrees in light of Applicant’s definition of “summary” that Merkulov does not disclose any summarization operation that generates a summary from a character string, let alone calculate a second probability based on the summary and obtain a second determination result (i.e., based on the second probability, which is tied to the summary) as required by the claims. Notably, Wang does not cure these deficiencies.
The Examiner hereby asserts that the totality of the evidence neither anticipates nor renders obvious the particular combination of elements as claimed above. The combination of features as claimed would not have been obvious to one of ordinary skill in the art because any combination of the evidence at hand to reach the combination of features as claimed would require a substantial reconstruction of Applicant’s claimed invention relying on improper hindsight bias. Lastly, the Examiner incorporates Applicant’s arguments on pages 15-17 here.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nagar (US 2020/0193493) discloses NLP processing used in determining when product items within a catalog contain incorrect attribute values (see: 0016).
Kopru (US 20220327550) discloses using neural networks in identifying potentially fraudulent item listings (see: 0031, Fig. 1C, Fig. 2B, Fig. 3).
PTO form 892-U discusses using linear regression and training to address fraud in reputation systems (see: Introduction, Section 6, 6.2).
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WILLIAM J. ALLEN
Primary Examiner
Art Unit 3625
/WILLIAM J ALLEN/ Primary Examiner, Art Unit 3619
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