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 .
Specification
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 disclosure is objected to because of the following informalities: Paragraph 44 recites the phrase “the vendor name may be the same of different” in line 7.
Appropriate correction is required.
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 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 limitation(s) is/are: information acquisition unit, prompt generation unit, authenticity evaluation unit, and information update unit in claim 1. These limitations are supported by Paragraph 0023 which discloses “implemented by executing one or more computer programs with a processor, may be implemented by one or more hardware circuits (for example, FPGA or ASIC), or may be implemented by a combination thereof.”
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/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 this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/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.
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.
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because it is directed to a signal per se.
Examiner suggests amending the claim to specify the use of a non-transitory computer readable storage medium as is supported by Paragraph 23 of the specification.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) limitations which under their broadest reasonable interpretation are directed to certain methods of organizing human activity. This judicial exception is not integrated into a practical application as explained below. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception as explained below.
Regarding Claim 1, the claim recites an information construction apparatus comprising:
an information acquisition unit configured to acquire information of which authenticity is reserved as input information;
a prompt generation unit configured to, in a case where configuration information extracted from the input information is not included in configuration management information at least as a part of product management information regarding a single or a plurality of products, generate a prompt used to obtain a single or a plurality of element labels corresponding to the configuration information and input the prompt into a generative model;
an authenticity evaluation unit configured to calculate reliability of the element label for each of the single or the plurality of element labels, in a case where the single or the plurality of element labels is extracted from output data of the generative model; and
an information update unit configured to, in a case where the single or the plurality of extracted element labels includes one or more high-reliability labels, add a data set including the one or more high-reliability labels and the extracted configuration information to the configuration management information as an authenticity data set, wherein
the configuration information is information indicating a product configuration that is at least one of a name and a model number of a product,
the high-reliability label is an element label of which reliability satisfies a condition, and
each authenticity data set included in the configuration management information is a data set including one or more high-reliability labels and configuration information corresponding to the one or more high-reliability labels.
Claim Interpretation: Under the broadest reasonable interpretation, the terms of the claim are
presumed to have their plain meaning consistent with the specification as it would be interpreted by
one of ordinary skill in the art. See MPEP 2111.
Receiving information where the authenticity is unspecified. Humans regularly receive information where the authenticity of the information is unknown.
Using a generative AI model to label a product based on the extraction of a product name and model number if they were not found in the database. Humans regularly update product information tables and label items
Calculating a reliability for the label generated. Humans regularly evaluate how true a designation is
Updating the database based on the reliability of the label. Humans regularly update tables and can make a decision to update based on how trustworthy information is
Additional elements are information acquisition unit, prompt generation unit, generative model, authenticity evaluation unit and information update unit. Per the 112f interpretation, the information acquisition unit, prompt generation unit and authenticity evaluation unit are computer programs implemented on generic computer hardware.
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory
category. See MPEP 2106.03. The claim recites at least one step or act, including receiving
continuous training data. Thus, the claim is to a system, which is one of the statutory categories
of invention. (Step 1: YES).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a
judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception
when the judicial exception is “set forth” or “described” in the claim.
As discussed above the broadest reasonable interpretation of the claims as a whole is that the claim elements are directed to certain methods of organizing human activity. The claim as whole describes steps for updating a product database, including receiving new product information, labeling products, judging the reliability of the labels and updating the database. Updating the product database as recited in the claim can be performed mentally or in a computer is similar to “organizing human activity” as discussed in MPEP 2106.04(a)(2) Subsection II. (Step 2A Prong One: YES)
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole
integrates the recited judicial exception into a practical application of the exception or whether the
claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether
there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating
those additional elements individually and in combination to determine whether the claim as a whole
integrates the exception into a practical application. See MPEP 2106.04(d).
The additional elements recited are information acquisition unit, prompt generation unit, generative model, authenticity evaluation unit and information update unit. Per the 112f interpretation, the information acquisition unit, prompt generation unit and authenticity evaluation unit are computer programs implemented on generic computer hardware.
These additional elements provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amount to
significantly more than the recited exception, i.e., whether any additional element, or combination of
additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
At Step 2A, the additional elements recited were found to represent nothing more than mere instructions to apply the judicial exception on a computer using generic computer components. Mere instructions to “apply” the abstract ideas, cannot provide an inventive concept. See MPEP 2106.05(f). The analysis under Step 2A, Prong Two is carried through to Step 2B. The recited additional elements are well understood, routine and conventional. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. (Step 2B: NO).
As such Claim 1 is patent illegible.
The analysis above is applicable to Claims 1,8,9,14,15
Regarding Claim 2, a human can add the product information and label to a separate list with the determination that the label is not reliable enough.
Regarding Claim 3, a human can remove entries in a database based on the similarity determination
Regarding Claim 4, a human can remove entries in a database based on the similarity determination
Regarding Claim 5, a human can add how reliable they thought a label was to the database
Regarding Claim 6, a human can update their reliability metric based on receiving data that affirms their label
Regarding Claim 7, a human can perform similarity determinations and update both the temporary and permanent databases.
Regarding Claim 10, a human can follow rules to calculate a reliability metric
Regarding Claim 11, a human can determine if a rule was satisfied and calculate a reliability based on that
Regarding Claim 12, similar to Claim 2 and additionally a human can update rules they follow
Regarding Claim 13, a human can acquire the label they assigned from a database
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1, 8, 14, 15 are rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356).
Regarding Claim 1, Merkulov teaches an information construction apparatus comprising:
an information acquisition unit configured to acquire information( processing device obtains a data record comprising digital data for a product that includes a product description, a product category, and a source organization.[0073]) of which authenticity is reserved as input information(Review and approval of product submissions on a distributed online platform presented in multiple different geographic regions and multiple different languages around the world presents challenges of scale, proper categorization, and accurate verification(Interpretation: authenticity is reserved means that information could be authenticated));
in a case where configuration information(input data record from the user that includes a product name, product description, product type, source organization, and other metadata relating to the product.[0080]) extracted from the input information(The product approval system 150 performs pre-processing 204 to the data record 202. In some embodiments, the pre-processing 204 includes feature extraction[0050]) is not included in configuration management information(set of authorized product types[0062], Fig. 3 304) at least as a part of product management information regarding a single or a plurality of products( At operation 304, the processing device determines whether a product described in the data record received at operation 304 is an authorized product type. The processing device compares the product type to a set of authorized product types[0062]), obtain a single or a plurality of element labels corresponding to the configuration information(The second machine learning model produces one or more classifications[0065]);
an authenticity evaluation unit configured to calculate reliability of the element label for each of the single or the plurality of element labels, in a case where the single or the plurality of element labels is extracted from output data of the generative model(At operation 308, the processing device applies a second machine learning model to the data record received at operation 302. For instance, the second machine learning model is a trained classifier that receives the product type, product description and source organization extracted from the data record. The second machine learning model produces one or more classifications that include a confidence score for each classification produced. Each classification indicates a predicted category of the data record[0065]); and
an information update unit configured to, in a case where the single or the plurality of extracted element labels includes one or more high-reliability labels(classification that passes Fig 3 308 Threshold Confidence), add a data set including the one or more high-reliability labels and the extracted configuration information(Fig. 3 310 Approve, Fig. 7 discloses a dataset including extracting configuration information and labels/classifications that have passed the threshold and are high reliability) to the configuration management information as an authenticity data set(At operation 310(Fig. 3), the processing device assigns the data record an approval status indicating that the data record is approved. For example, the processing device annotates, such as by updating a metadata attribute of the data record to an approved status[0068].; set of approved products[0081]), wherein
the configuration information is information indicating a product configuration that is at least one of a name(Product Name: PTC MathCAD [Fig 7]),
the high-reliability label is an element label of which reliability satisfies a condition(Fig 3 308 Threshold Confidence), and
each authenticity data set included in the configuration management information is a data set including one or more high-reliability labels(Fig 7 Predicted Categories Simulation Software 0.987… [Fig 7]) and configuration information(Product Name and Product Description [Fig 7]) corresponding to the one or more high-reliability labels(Fig 7 discloses an example data entry including high reliability labels and configuration information).
Merkulov does not teach a prompt generation unit configured to generate a prompt used to obtain a single or a plurality of element labels, inputting the prompt into a generative model to output the label data and the configuration information includes a model number of a product.
However, Xuan teaches a prompt generation unit configured to generate a prompt(the online concierge system 140 can generate a prompt using the external data as context[0040]) used to obtain a single or a plurality of element labels, inputting the prompt into a generative model to output the label data(an online system may provide an instruction prompt that includes chain-of-thoughts instructions and examples for the machine-learned language model to follow and automatically generate labels based on the data provided to the language model.[0002], The labels may be used for item categorization[0038]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Merkulov with the generative AI of Xuan because it would reduce the manual work and increase the accuracy of generated labels(Xuan 0080).
Although Merkulov teaches a configuration information includes the product name, it does not explicitly teach the configuration information includes a model number of a product.
Xuan teaches the configuration information includes a model number of a product (Additionally, item data may also include attributes of items such as the size, color, weight, stock keeping unit (SKU), or serial number for the item.[0047]).
It would have been obvious to the PHOSITA having the teachings of Merkulov to have the concept of Xuan before the effective filing date because using the model number associated product name is so well known in the art and the model number is a unique identifier.
Claims 14 and 15 recite similar limitations to Claim 1 and are rejected under the same rationale.
Regarding Claim 8, Merkulov teaches each element label is a configuration information label that is a label of a category to which the product configuration belongs(“Simulation Software” Block 708 in Figure 7) or a vendor name that is a vendor of the product.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) as applied to claim 1 above, and further in view of Dronen(EP 3543906).
Regarding Claim 2, Merkulov in view of Xuan teaches in a case where the single or the plurality of extracted element labels includes one or more low-reliability labels and the low-reliability label is an element label of which reliability does not satisfy a condition(Step 308 -> NO [Figure 3 Merkulov]). Merkulov also teaches adding a data set including one or more labels and the extracted configuration information to management information(Fig 7 teaches a dataset including one or more labels/classifications and the extracted configuration information).
Merkulov in view of Xuan does not teach the information update unit adds a data set temporary management information as a temporary data set, each temporary data set included in the temporary management information corresponding to the one or more low-reliability labels.
However, Dronen the information update unit adds a data set temporary management information as a temporary data set (sensor data(mapped to label) is marked to indicate that the confidence metric for the feature detected in the sensor data is below the confidence threshold; and store the sensor data in a temporary storage[Exemplary embodiment 13]), each temporary data set included in the temporary management information is a data set(temporary storage[Exemplary embodiment 13]) corresponding to the one or more low-reliability labels(sensor data is below the confidence threshold[Exemplary embodiment 13] in view of (Step 308 -> NO [Figure 3 Merkulov])).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to combine the system of Merkulov in view of Xuan with the temporary database of Dronen because it would improve feature detection(Dronen).
Claim(s) 3, 4, 5 are rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) in view of Dronen(EP 3543906) as applied to claim 2 above, and further in view of Menestrina(Generic Entity Resolution with Data Confidences).
Regarding Claim 3, prior references teach the information update unit performs similarity determination as to whether or not a target temporary data set that is a temporary data set that matches or is similar to an extracted data set including the single or the plurality of extracted element labels and the extracted configuration information is the temporary management information(At operation 304, the processing device determines whether a product described in the data record received at operation 304 is an authorized product type. The processing device compares the product type to a set of authorized product types[Merkulov 0062] in view of temporary storage[ Dronen Exemplary embodiment 13]).
Prior references do not teach in a case where a result of the similarity determination is true, the information update unit deletes a low-reliability label that matches or is similar to any one of the one or more high-reliability labels added to the configuration management information of the single or the plurality of extracted element labels, from the target temporary data set.
However, Menestrina teaches in a case where a result of the similarity determination is true, the information update unit deletes a low-reliability label that matches or is similar to any one of the one or more high-reliability labels added to the configuration management information of the single or the plurality of extracted element labels(We say that a record r dominates a record s, denoted s ≤ r, if the following two conditions hold: 1. s.A ⊆ r.A(Interpretation: attribute(A) is one or more labels) 2. s.C ≤ r.C(Clarification: C here is confidence), “A significant performance improvement is to discard a dominated record as soon as it is found in the resolution process”[5. Domination]), from the target temporary data set.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Merkulov, Xuan, and Dronen with the data pruning of Menestrina because it would offer a significant performance improvement(Menestrina).
Regarding Claim 4, prior references teach configuration information in the target temporary data set matches the configuration information in the extracted data set(At operation 304, the processing device determines whether a product described in the data record received at operation 304 is an authorized product type. The processing device compares the product type to a set of authorized product types[Merkulov 0062] in view of temporary storage[ Dronen Exemplary embodiment 13])..
Regarding Claim 5, Merkulov teaches each temporary data set included in the temporary management information includes calculated reliability, for each element label included in the temporary data set(708 in Figure 7 of Merkulov discloses including calculated reliability in a dataset).
Claim(s) 6 is rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) in view of Dronen(EP 3543906) in view of Menestrina(Generic Entity Resolution with Data Confidences) as applied to claim 5 above, and further in view of Gudupally(US PGPub 20230410176).
Regarding Claim 6, prior references do not teach regarding each element label in the extracted data set, in a case where the calculated reliability of the element label is higher than reliability of an element label that matches or is similar to the element label, in the target temporary data set, the information update unit updates the reliability in the target temporary data set to the calculated reliability.
However, Gudapally teaches in a case where the calculated reliability of the element label is higher than reliability of an element label that matches or is similar to the element label, in the target temporary data set, the information update unit updates the reliability in the target temporary data set to the calculated reliability(When the priority score for the new value exceeds the priority score for the existing value, the new value can replace the existing value in the content catalog. When the priority score for the new value does not exceed the priority score for the existing value, the existing value can be retained in the product catalog. The process of determining whether to overriding or not overriding existing values with new values can be referred to a “merging,” as some of the new values are “merged” into content catalog."[0067]. Interpretation: priority score here is dependent on the art’s confidence score and is a measure of reliability. ).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Merkulov, Xuan, Dronen and Menestrina to combine the conditional merge of Gudupally because it would allow for existing content to be updated(Gudapally 0079).
Claim(s) 9 is rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) as applied to claim 1 above, and further in view of Mesde(US Pat 12524232).
Regarding Claim 9, Merkulov teaches data records in relation to software(Fig 7).
Neither Merkulov nor Xuan teach the product management information is a software bill of materials (SBOM).
However, Mesde teaches the product management information is a software bill of materials (SBOM)( the SBOM source A 123A may be a product lifecycle management (PLM) system[Col 6 Line 67 – Col 7 Line 1]).
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to combine the system of Merkulov in view of Xuan with the SBOM of Mesde because it would enable auditability of software(Mesde[Col 16 Line 54]).
Claim(s) 10, 11 are rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) as applied to claim 1 above, and further in view of Nascimento(Configurable assembly of classification rules for enhancing entity resolution results).
Regarding Claim 10, Merkulov teaches calculating the reliability of the element label for at least one of the single or the plurality of extracted element labels.
Neither Merkulov nor Xuan teach calculating reliability on a rule basis.
However, Nascimento teaches calculating reliability on a rule basis(we employ a function hcs in order to generate a confidence score hcs(R, (e1, e2)) for each rule R ∈ A ∪ , such that hcs(R, (e1, e2)) ∈ [0, 1]., we employ a function (fagg) in order to aggregate the confidence scores computed in Step 1 (i.e., ) to generate a final confidence score [Algorithm 1]).
It would have been obvious to one of ordinary skill before the effective filing date to combine the system of Merkulov in view of Xuan with the rules based confidence scoring of Nascimento because it would protect against data quality problems(Nascimento Abstract).
Regarding Claim 11, Merkulov teaches calculating reliability for at least one of the single or the plurality of extracted element labels.
Neither Merkulov nor Xuan teach whether or not any one or more of a plurality of evaluation rules associated with a point is satisfied, for at least one of the single or the plurality of extracted element labels and calculates the reliability based on a point corresponding to each of the one or more satisfied evaluation rules.
However Nascimento teaches whether or not any one or more of a plurality of evaluation rules associated with a point is satisfied(we employ a function hcs in order to generate a confidence score hcs(R, (e1, e2)) for each rule R ∈ A ∪ , such that hcs(R, (e1, e2)) ∈ [0, 1].[Algorithm 1]), for at least one of the single or the plurality of extracted element labels and calculates the reliability based on a point corresponding to each of the one or more satisfied evaluation rules(we employ a function (fagg) in order to aggregate the confidence scores computed in Step 1 (i.e., ) to generate a final confidence score [Algorithm 1]).
It would have been obvious to one of ordinary skill before the effective filing date to combine the system of Merkulov in view of Xuan with the rules based confidence scoring of Nascimento because it would protect against data quality problems(Nascimento Abstract).
Claim(s) 12 is rejected under 35 U.S.C. 103 as being Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) in view of Dronen(EP 3543906) as applied to claim 2 above(Claim 12 is dependent on Claim 1, but contains identical limitations to Claim 2), and further in view of Jonna(US PGPub 20220019419).
Regarding Claim 12, prior references do not teach in a case where the information update unit specifies that low reliability of a certain element label is maintained from the temporary management information, the information update unit updates an evaluation rule regarding the certain element label.
However, Jonna teaches in a case where the information update unit specifies that low reliability of a certain element label is maintained from the temporary management information(If the trust score is below the threshold, the deployment evaluation system 104 may perform a repair process, as indicated by block 514[0095]), the information update unit updates an evaluation rule(In some cases, for instance, the deployment evaluation system 104 may identify why the proposed upgrade met certain criteria used to generate the trust score. The deployment evaluation system 104 may then attempt to repair these issues[0095]) regarding the certain element label.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Merkulov, Xuan, and Dronen with the trust score criteria repair of Jonna because it would allow the system to verify if it is working correctly(Jonna 0095).
Claim(s) 13 is rejected under 35 U.S.C. 103 as being unpatentable over Merkulov(US PGPub 20230252544) in view of Xuan(US PGPub 20250200356) in view of Dronen(EP 3543906) in view of Menestrina(Generic Entity Resolution with Data Confidences) as applied to claim 3 above, and further in view of Kuan (US PGPub 20240362409).
Regarding Claim 13, prior references teach in a case where a temporary data set including the extracted configuration information is in the temporary management information(At operation 304, the processing device determines whether a product described in the data record received at operation 304 is an authorized product type. The processing device compares the product type to a set of authorized product types[Merkulov 0062] in view of temporary storage[ Dronen Exemplary embodiment 13]) and prompt generation (the online concierge system 140 can generate a prompt using the external data as context[0040]).
Prior references do not teach generating a prompt used to obtain the low-reliability label in the temporary data set for the configuration information.
However, Kuan teaches generating a prompt used to obtain the low-reliability label in the temporary data set for the configuration information(generate a text prompt configured for input to a large language model, with the text prompt being formatted and configured to include information relevant to the large language model… The text prompt may be processed by a large language model to generate code used to extract relevant portions of data(low-reliability label corresponding to the configuration information) from the database(temporary management database), and the code is executed on the database.[0004]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Merkulov, Manchanda, Dronen and Menestrina with the prompt based database querying of Kuan because it would provide increased flexibility and utility(Kuan 0006).
No Art Rejection Subject Matter
There is no are rejection being applied in this Office Action because none of the prior art teaches “in a case where the result of the similarity determination is true and the target temporary data set includes one or more element labels, of which reliability does not satisfy a condition, included in the target temporary data set, and reliability calculated for an element label that matches or is similar to the element label of the extracted data set satisfies the condition, for each of the one or more element labels, the information update unit adds the extracted data set and/or the target temporary data set to the configuration management information”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Chong(US PGPub 20140379616) teaches a product classifier using confidence scores.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARJUN R SWAMY whose telephone number is (571)272-9763. The examiner can normally be reached Mon-Fri 8-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hai Phan can be reached at (571) 272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ARJUN SWAMY/Examiner, Art Unit 2654
/HAI PHAN/Supervisory Patent Examiner, Art Unit 2654
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