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 .
Status of the Claims
Claims 1-16 are currently pending. Claim 16 is newly added in the Claims filed on April 23, 2026.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on January 22, 2025 was previously considered by Examiner as part of the Non-Final Rejection mailed on February 11, 2026, with the exception of KR 10-2012-0105916 A, KR 10-2022-0111055 A, and KR 10-2023-0033365 A, because the aforementioned references are cited in the International Search Report (ISR) document filed on January 22, 2025, and indicated as documents of particular relevance (“Y” references), but Applicant had not provided any translations beyond the Abstracts for the aforementioned references. 37 CFR 1.98 requires “a concise explanation of the relevance, as it is presently understood by the individual designated in §1.56(c) most knowledgeable about the content of the information, of each patent, publication, or other information listed that is not in the English language.” However, the translated Abstracts alone are not sufficient to determine the relevancy of the aforementioned references. Examiner further notes that translations for the aforementioned references are still not present in the file folder for the present application. Hence, the aforementioned references have not yet been considered and will not be considered until translations for the references are provided.
Claim Objections
Claim 16 is objected to because of the following informalities: Claim 16 recites “</u>” in two separate locations (at the end of the “acquiring individual correlation information” and “acquiring survey data acquisition time” steps). These appear to be typographical errors. Appropriate correction is required.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
Claims 1-16 are within the four statutory categories. Claims 1-10 and 16 are drawn to methods for pricing data to be sold, which is within the four statutory categories (i.e. process). Claims 11-14 are drawn to a device for pricing data to be sold, which is within the four statutory categories (i.e. machine). Claim 15 is drawn to a non-transitory medium for pricing data to be sold, which is within the four statutory categories (i.e. manufacture).
Prong 1 of Step 2A
Claim 1, which is representative of the inventive concept, recites: A method for providing price information for health data, comprising:
acquiring sensitivity information indicating a degree of sensitivity to a plurality of pieces of health data and survey data from a plurality of surveys including asking price information for the plurality of pieces of health data;
acquiring individual correlation information that represents an individual correlation of asking price relative to sensitivity in each of the plurality of surveys based on the survey data;
acquiring a correlation trend indicator that represents an overall correlation of the asking price relative to sensitivity based on a regression result of the individual correlation information; and
providing price information determined for the plurality of pieces of health data based on the correlation trend indicator.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite fundamental economic practices (i.e. hedging, insurance, mitigating risk – in this case, the limitations of acquiring sensitivity information, individual correlation information, and a correlation trend indicator, and providing price information based on the correlation trend indicator recite offer-based price optimization), and/or managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions – in this case, the limitations of acquiring sensitivity information, individual correlation information, and a correlation trend indicator, and providing price information based on the correlation trend indicator recite following rules or instructions to optimize pricing information), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for Claims 11 and 15-16 is identical as the abstract idea for Claim 1, because the only difference between Claims 1, 11, and 15 is that Claim 1 recites a method, whereas Claim 11 recites a device and Claim 15 recites a non-transitory computer-readable medium. Additionally, Claim 16 includes all the limitations of Claim 1, and further incorporates the limitations recited in dependent Claims 4-5, 7, and 10, which merely further recite limitations that narrow the abstract idea, as is further discussed below with regards to dependent Claims 4-5, 7, and 10.
Dependent Claims 2-10 and 12-15 include other limitations, for example Claims 2 and 12 recite types of asking price information, Claims 3 and 13 recite types of price information and health data, Claims 4 and 14 recite using the sensitivity as an independent variable and the asking price as a dependent variable to obtain the correlation trend indicator, Claim 5 recites that the correlation trend indicator is determined by a linear regression function, Claims 6-7 recites types of data used to obtain the price information, Claims 8-9 recite types of data used to obtain the individual correlation information, Claim 10 recites limitations pertaining to the survey data, and Claim 15 recites the invention of Claim 1 but embodied as a non-transitory computer-readable medium, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04, and/or do not further narrow the abstract idea and instead only recite additional elements, which will be further addressed below. Hence dependent Claims 2-10 and 12-15 are nonetheless directed towards fundamentally the same abstract idea as independent Claims 1 and 11.
Hence Claims 1-15 recite the aforementioned abstract idea.
Prong 2 of Step 2A
Claims 1 and 11 are not integrated into a practical application because the additional elements (i.e. the non-underlined limitations above – in this case, any computer/device structural limitations recited to perform the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of a device including a computer, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see [0043] and [0086]-[0087] of the as-filed Specification, and see MPEP 2106.05(f); and/or
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language reciting that the processed data is health data, which amounts to limiting the abstract idea to the field of healthcare, e.g. see MPEP 2106.05(h).
Additionally, dependent Claims 2-10 and 12-15 include other limitations, but these limitations also amount to no more than mere instructions to apply an exception (e.g. the non-transitory computer-readable medium recited in dependent Claim 15), generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data recited in dependent Claims 2-4, 6-10, and 12-14), and/or do not include any additional elements beyond those already recited in independent Claims 1 and 11, and hence also do not integrate the aforementioned abstract idea into a practical application.
Hence Claims 1-15 do not include additional elements that integrate the judicial exception into a practical application.
Step 2B
Claims 1 and 11 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, any computer/device structural limitations recited to perform the abstract idea), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, and/or generally link the abstract idea to a particular technological environment or field of use, wherein the additional elements comprise limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The present Specification expressly disclosing that the structural additional elements are well-understood, routine, and conventional in nature:
[0043] and [0086]-[0087] of the as-filed Specification discloses that the additional elements (i.e. the computer/device structural limitations recited to perform the abstract idea) comprise a plurality of different types of generic computing systems;
Dependent Claims 2-10 and 12-15 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because the additional elements recited in the aforementioned dependent claims similarly amount to mere instructions to apply the exception (e.g. the non-transitory computer-readable limitation recited in dependent Claim 15), generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data recited in dependent Claims 2-4, 6-10, and 12-14), and/or do not recite any additional elements not already recited in independent Claims 1 and 11, and hence do not amount to “significantly more” than the abstract idea.
Hence, Claims 1-15 do not include any additional elements that amount to “significantly more” than the judicial exception.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, Claims 1-15 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 8, 11-13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Gardner (US 2007/0050201) in view of Mishra (US 2015/0154646).
Regarding Claim 1, Gardner teaches the following: A method for providing price information for health data, comprising:
acquiring sensitivity information indicating a degree of sensitivity and survey data from a plurality of surveys including asking price information (The system obtains customer data from a plurality of questionnaires or surveys, e.g. see Gardner [0073], Figs. 4a-4e. Furthermore, the data obtained includes sensitivity measures between product features, price, and service, e.g. see Gardner [0073], [0094], and [0139]-[0140].);
acquiring individual correlation information that represents an individual correlation of asking price relative to sensitivity in each of the plurality of surveys based on the survey data (The system analyzes the customer survey data relative to the customer’s actions – for example, the customer may indicate that they are not influenced by price, but their actions show that they are indeed sensitive to price, e.g. see Gardner [0094] and [0139]-[0140]. That is, the system determines the correlation between a user’s survey answers including price data and the user’s behavior.);
acquiring a correlation trend indicator that represents an overall correlation of the asking price relative to sensitivity based on a regression result of the individual correlation information (The system performs regression analysis on the customer behavior and generates a model (i.e. a correlation trend indicator) that identifies a correlation between the customer behavior and successful outcomes in terms of acceptance by a provider, e.g. see Gardner [0094]-[0095].); and
providing price information determined based on the correlation trend indicator (The model (i.e. the correlation trend indicator) is used to filter results to be presented to the user, wherein the results presented (i.e. provided) include products and their respective prices, e.g. see Gardner [0094] and [0112], Fig. 4d.).
But Gardner does not teach and Mishra teaches the following:
wherein the sensitivity and asking price information are for a plurality of pieces of health data (The system includes a plurality of databases that store various patient data including medical data, e.g. see Mishra [0033], and market valuations for the data including mechanisms for pricing the data and an indication of the sensitivity of the data, e.g. see Mishra [0049] and [0067].); and
wherein the provided price information is for the plurality of pieces of health data (The system includes a plurality of databases that store various patient data including medical data, e.g. see Mishra [0033], and market valuations for the data including mechanisms for pricing the data and an indication of the sensitivity of the data, e.g. see Mishra [0049] and [0067].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify Gardner to incorporate the healthcare data as the product being sold as taught by Mishra in order to match user needs, e.g. see Mishra [0006]-[0008], [0030], and [0066].
Regarding Claim 2, the combination of Gardner and Mishra teaches the limitations of Claim 1, and Gardner and Mishra teach the following: The method for providing price information for health data of Claim 1,
wherein the asking price information includes:
first asking price information corresponding to types of the plurality of pieces of health data (The system provides prices for different types of services filtered based on user preferences, e.g. see Gardner [0110]-[0112], Fig. 4d, wherein the services include data pertaining to medical services, e.g. see Mishra [0031].); and
second asking price information corresponding to periods of time collecting the plurality of pieces of health data (The prices for the services may be for services performed on a service time, e.g. see Gardner [0005], [0045], and [0134].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify Gardner to incorporate the healthcare data as the product being sold as taught by Mishra in order to match user needs, e.g. see Mishra [0006]-[0008], [0030], and [0066].
Regarding Claim 3, the combination of Gardner and Mishra teaches the limitations of Claim 1, and Gardner and Mishra teach the following: The method for providing price information for health data of Claim 1,
wherein the process of providing the determined price information includes:
providing type-specific price information corresponding to the types of the plurality of pieces of health data (The system provides prices for different types of services filtered based on user preferences, e.g. see Gardner [0110]-[0112], Fig. 4d, wherein the services include data pertaining to medical services and medical data, e.g. see Mishra [0031].); and
providing period-specific price information corresponding to the periods of time collecting the plurality of pieces of health data (The prices for the services may be for services performed on a service time, e.g. see Gardner [0005], [0045], and [0134].),
wherein the plurality of pieces of health data includes at least one of nutritional status, exercise status, skin condition, eating habits, personal characteristic information, health management information, and hereditary data (The types of data include medical data, e.g. see Mishra [0031], wherein the medical data includes data for nutritional profiling, social activities including in a gym, progression of a disease, and delineate genetic linkages using genomics and biomarkers, e.g. see Mishra [0034].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify Gardner to incorporate the types of healthcare data as taught by Mishra in order to match user needs, e.g. see Mishra [0006]-[0008], [0030], and [0066].
Regarding Claim 8, the combination of Gardner and Mishra teaches the limitations of Claim 1, and Gardner and Mishra further teach the following: The method for providing price information for health data of Claim 1,
wherein the process of acquiring the individual correlation information includes:
acquiring a plurality of pieces of additional health data that represents individual-specific characteristics (The system obtains personal data for customers including healthcare, biological, demographic, financial, user survey, and other medical data, e.g. see Mishra [0033], [0049], and [0067].); and
acquiring the individual correlation information based on the plurality of pieces of additional health data (The system analyzes the customer survey data relative to the customer’s actions – for example, the customer may indicate that they are not influenced by price, but their actions show that they are indeed sensitive to price, e.g. see Gardner [0094] and [0139]-[0140].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify Gardner to incorporate the types of healthcare data as taught by Mishra in order to match user needs, e.g. see Mishra [0006]-[0008], [0030], and [0066].
Regarding Claims 11 and 15, the limitations of Claims 11 and 15 are substantially similar to those claimed in Claim 1, with the sole difference being that Claim 1 recites a method, whereas Claim 11 recites a device, and Claim 15 recites a non-transitory computer-readable storage medium. Specifically pertaining to Claims 11 and 15, Examiner notes that Gardner teaches a system executing software modules, e.g. see Gardner [0038] and [0041], Figs. 3 and 6, and hence the grounds of rejection provided above for Claim 1 are similarly applied to Claims 11 and 15.
Regarding Claims 12-13, the limitations of Claims 12-13 are substantially similar to those claimed in Claims 2-3, with the sole difference being that Claims 2-3 recite a method, whereas Claims 12-13 recite a device. Specifically pertaining to Claims 12-13, Examiner notes that Gardner teaches a system executing software modules, e.g. see Gardner [0038] and [0041], Figs. 3 and 6, and hence the grounds of rejection provided above for Claims 2-3 are similarly applied to Claims 12-13.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gardner and Mishra in view of Callioni (US 2014/0006109).
Regarding Claim 4, the combination of Gardner and Mishra teaches the limitations of Claim 1, but does not teach and Callioni teaches the following: The method for providing price information for health data of Claim 1,
wherein in the process of acquiring the correlation trend indicator, the sensitivity is used as an independent variable and the asking price is used as a dependent variable to acquire the correlation trend indicator (The system constructs a plot with price power (i.e. asking price) on the y-axis (i.e. a dependent variable), e.g. see Callioni Fig. 43, wherein pricing power factors include price sensitivity, e.g. see Callioni [0147] and [0260]. That is, the price power (i.e. the asking price) is dependent on price sensitivity.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify the combination of Gardner and Mishra to incorporate using the sensitivity to determine the price power as taught by Callioni because sensitivity is useful for market analyses, research purposes, and decision making for manufacturers, e.g. see Callioni [0090].
Regarding Claim 14, the limitations of Claim 14 are substantially similar to those claimed in Claim 4, with the sole difference being that Claim 4 recites a method, whereas Claim 14 recites a device. Specifically pertaining to Claim 14, Examiner notes that Gardner teaches a system executing software modules, e.g. see Gardner [0038] and [0041], Figs. 3 and 6, and hence the grounds of rejection provided above for Claim 4 are similarly applied to Claim 14.
Claims 5, 7, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gardner, Mishra, and Callioni in view of Behlouli (US 2013/0006712).
Regarding Claim 5, the combination of Gardner, Mishra, and Callioni teaches the limitations of Claim 4, but does not teach and Behlouli teaches the following: The method for providing price information for health data of Claim 4,
wherein the correlation trend indicator is determined by a linear regression function based on the regression result (The system determines market trends utilizing a linear regression model between market price and time combined with a Meier smoothing algorithm to improve the correlation between variables, e.g. see Behlouli [0085].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify the combination of Gardner, Mishra, and Callioni to incorporate performing linear regression to determine market trends as taught by Behlouli in order to improve the correlation between variables, e.g. see Behlouli [0085].
Regarding Claim 7, the combination of Gardner, Mishra, Callioni, and Behlouli teaches the limitations of Claim 5, and Gardner and Mishra further teach the following: The method for providing price information for health data of Claim 1,
wherein the process of providing the determined price information includes:
acquiring survey data acquisition time for each of the plurality of surveys (The data stored by the system includes user surveys, e.g. see Mishra [0049], wherein the data may be time-stamped, e.g. see Mishra [0033].);
determining reliability of the survey data (The system evaluates customer behavior data to classify behavior types, wherein a behavior type may indicate that a customer’s actions do not match the customer’s submitted beliefs (i.e. reliability of survey data), e.g. see Gardner [0094].); and
updating the determined price information based on the survey data acquisition time and the reliability (The system determines the results to be presented to customers including price data for a service based on a model constructed based on the customer behavior type, e.g. see Gardner [0094] and [0112], Fig. 4d, wherein the data may be updated over time, e.g. see Gardner [0078].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of commerce to modify the combination of Gardner, Callioni, and Behlouli to incorporate the survey data acquisition as taught by Mishra in order to assess the quality of the data and provide accurate analyses, e.g. see Mishra [0052].
Regarding Claim 10, the combination of Gardner, Mishra, Callioni, and Behlouli teaches the limitations of Claim 7, and Gardner and Mishra further teach the following: The method for providing price information for health data of Claim 7,
wherein the survey data acquisition time refers to when all the survey data for the plurality of surveys has been acquired (The data stored by the system includes user surveys, e.g. see Mishra [0049], wherein all the data may be evaluated and time-stamped, e.g. see Mishra [0033] and [0038].), and
the reliability of the survey data is determined based on a number of pieces of the survey data, participation rate, survey period, and survey response speed (The system obtains a measure of how reliable the user input is based on comparing the user expressed beliefs with actual actions, e.g. see Gardner [0094], and the system receives user inputs (i.e. a number of pieces of survey data), e.g. see Mishra [0042]. Furthermore, the “participation rate” may be interpreted as the receipt of the user input, as this would indicate a participation rate of 100%, the “survey period” may be interpreted as the period in which the user provides the inputs, and the “survey response speed” may be interpreted as the time it took the user to provide the input. That is, given the broadest reasonable interpretation, Gardner and Mishra teach that the reliability is “based on” the number of pieces of survey data, participation rate, survey period, and survey response speed in that they each teach receiving user answers to surveys comprising at least one piece of data, provided at a 100% response rate, during some time period, after some amount of time.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of commerce to modify the combination of Gardner, Callioni, and Behlouli to incorporate determining the reliability based on the user inputs to the survey as taught by Mishra in order to assess the quality of the data and provide accurate analyses, e.g. see Mishra [0052].
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gardner and Mishra in view of O’Beirne (US 2014/0372242).
Regarding Claim 6, the combination of Gardner and Mishra teaches the limitations of Claim 1, but does not teach and O’Beirne teaches the following: The method for providing price information for health data of Claim 1,
wherein the process of providing the determined price information includes:
acquiring actual purchasing frequency and purchase price information corresponding to each of the plurality of pieces of health data from an external server (The system tracks the frequency of sales of a number of information blocks, e.g. see O’Beirne [0016] and [0061], wherein the system includes interface hardware for connecting to external systems, such as distributers of the data, e.g. see O’Beirne [0097].); and
updating the determined price information based on the actual purchasing frequency and purchase price information (The system updates the selling price of the data based on a sales frequency of the data, e.g. see O’Beirne [0016] and [0061.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of commerce to modify the combination of Gardner and Mishra to incorporate updating the selling price based on the purchasing frequency as taught by O’Beirne in order to increase profits, e.g. see O’Beirne [0065].
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gardner and Mishra in view of Bardis (US 2007/0050208).
Regarding Claim 9, the combination of Gardner and Mishra teaches the limitations of Claim 8, and Gardner and Mishra further teach the following: The method for providing price information for health data of Claim 8,
wherein the plurality of pieces of additional health data includes at least one of the presence or absence of disease, gender, income, and age (The system obtains personal data for customers including healthcare, biological, demographic, financial, user survey, and other medical data that is used for the prediction and intervention in the progression of a disease, e.g. see Mishra [0033], [0049], and [0067].).
But the combination of Gardner and Mishra does not teach and Bardis teaches the following:
the asking prices relative to sensitivity are determined to have a positive relationship between the sensitivity information and the asking price information (The system includes a price and a sensitivity, wherein the sensitivity indicates an increase in profit for an increase in price of an item, e.g. see Bardis [0082].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of commerce to modify the combination of Gardner and Mishra to incorporate the positive relationship between the price and sensitivity as taught by Bardis in order to enable vendors to better understand their pricing strategy, e.g. see Bardis [0100].
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Gardner in view of Mishra, further in view of Callioni and Behlouli.
Regarding Claim 16, Gardner teaches the following: A method for providing price information for health data, comprising:
acquiring sensitivity information indicating a degree of sensitivity and survey data from a plurality of surveys including asking price information (The system obtains customer data from a plurality of questionnaires or surveys, e.g. see Gardner [0073], Figs. 4a-4e. Furthermore, the data obtained includes sensitivity measures between product features, price, and service, e.g. see Gardner [0073], [0094], and [0139]-[0140].);
acquiring individual correlation information that represents an individual correlation of asking price relative to sensitivity in each of the plurality of surveys based on the survey data (The system analyzes the customer survey data relative to the customer’s actions – for example, the customer may indicate that they are not influenced by price, but their actions show that they are indeed sensitive to price, e.g. see Gardner [0094] and [0139]-[0140]. That is, the system determines the correlation between a user’s survey answers including price data and the user’s behavior.);
acquiring a correlation trend indicator that represents an overall correlation of the asking price relative to sensitivity based on a regression result of the individual correlation information (The system performs regression analysis on the customer behavior and generates a model (i.e. a correlation trend indicator) that identifies a correlation between the customer behavior and successful outcomes in terms of acceptance by a provider, e.g. see Gardner [0094]-[0095].);
providing price information determined based on the correlation trend indicator (The model (i.e. the correlation trend indicator) is used to filter results to be presented to the user, wherein the results presented (i.e. provided) include products and their respective prices, e.g. see Gardner [0094] and [0112], Fig. 4d.);
determining reliability of survey data (The system evaluates customer behavior data to classify behavior types, wherein a behavior type may indicate that a customer’s actions do not match the customer’s submitted beliefs (i.e. reliability of survey data), e.g. see Gardner [0094].); and
updating the determined price information based on the survey data acquisition time and the reliability (The system determines the results to be presented to customers including price data for a service based on a model constructed based on the customer behavior type, e.g. see Gardner [0094] and [0112], Fig. 4d, wherein the data may be updated over time, e.g. see Gardner [0078].).
But Gardner does not teach and Mishra teaches the following:
wherein the sensitivity and asking price information are for a plurality of pieces of health data (The system includes a plurality of databases that store various patient data including medical data, e.g. see Mishra [0033], and market valuations for the data including mechanisms for pricing the data and an indication of the sensitivity of the data, e.g. see Mishra [0049] and [0067].);
wherein the provided price information is for the plurality of pieces of health data (The system includes a plurality of databases that store various patient data including medical data, e.g. see Mishra [0033], and market valuations for the data including mechanisms for pricing the data and an indication of the sensitivity of the data, e.g. see Mishra [0049] and [0067].);
acquiring survey data acquisition time for each of the plurality of surveys (The data stored by the system includes user surveys, e.g. see Mishra [0049], wherein the data may be time-stamped, e.g. see Mishra [0033].),
wherein the survey data acquisition time refers to when all the survey data for the plurality of surveys has been acquired (The data stored by the system includes user surveys, e.g. see Mishra [0049], wherein all the data may be evaluated and time-stamped, e.g. see Mishra [0033] and [0038].), and
the reliability of the survey data is determined based on the number of pieces of the survey data, participation rate, survey period, and survey response speed (The system obtains a measure of how reliable the user input is based on comparing the user expressed beliefs with actual actions, e.g. see Gardner [0094], and the system receives user inputs (i.e. a number of pieces of survey data), e.g. see Mishra [0042]. Furthermore, the “participation rate” may be interpreted as the receipt of the user input, as this would indicate a participation rate of 100%, the “survey period” may be interpreted as the period in which the user provides the inputs, and the “survey response speed” may be interpreted as the time it took the user to provide the input. That is, given the broadest reasonable interpretation, Gardner and Mishra teach that the reliability is “based on” the number of pieces of survey data, participation rate, survey period, and survey response speed in that they each teach receiving user answers to surveys comprising at least one piece of data, provided at a 100% response rate, during some time period, after some amount of time.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify Gardner to incorporate the healthcare data as the product being sold and the time-related metrics as taught by Mishra in order to match user needs, e.g. see Mishra [0006]-[0008], [0030], and [0066], and in order to assess the quality of the data and provide accurate analyses, e.g. see Mishra [0052].
But the combination of Gardner and Mishra does not teach and Callioni teaches the following:
wherein in the process of acquiring the correlation trend indicator, the sensitivity is used as an independent variable and the asking price is used as a dependent variable to acquire the correlation trend indicator (The system constructs a plot with price power (i.e. asking price) on the y-axis (i.e. a dependent variable), e.g. see Callioni Fig. 43, wherein pricing power factors include price sensitivity, e.g. see Callioni [0147] and [0260]. That is, the price power (i.e. the asking price) is dependent on price sensitivity.).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify the combination of Gardner and Mishra to incorporate using the sensitivity to determine the price power as taught by Callioni because sensitivity is useful for market analyses, research purposes, and decision making for manufacturers, e.g. see Callioni [0090].
But the combination of Gardner, Mishra, and Callioni does not teach and Behlouli teaches the following:
wherein the correlation trend indicator is determined by a linear regression function based on the regression result (The system determines market trends utilizing a linear regression model between market price and time combined with a Meier smoothing algorithm to improve the correlation between variables, e.g. see Behlouli [0085].).
Furthermore, before the effective filing date, it would have been obvious to one ordinarily skilled in the art of providing services to modify the combination of Gardner, Mishra, and Callioni to incorporate performing linear regression to determine market trends as taught by Behlouli in order to improve the correlation between variables, e.g. see Behlouli [0085].
Response to Arguments
Applicant’s arguments, see Remarks, filed April 23, 2026, with respect to the considerations regarding the KR 10-2012-0105916 A, KR 10-2022-0111055 A, and KR 10-2023-0033365 A references have been fully considered but are not persuasive. Although Applicant states that translations of the aforementioned references have been submitted, the translations do not appear in the file folder. Hence, the aforementioned references will not be considered until the translations are provided.
Applicant’s arguments, see Remarks, filed April 23, 2026, with respect to the rejections of Claims 8 and 10 under 35 U.S.C. 112(b) have been fully considered and, in combination with the claim amendments, are persuasive. The rejections of Claims 8 and 10 under 35 U.S.C. 112(b) has been withdrawn.
Applicant’s arguments, see Remarks, filed April 23, 2026, with respect to the rejections of Claims 1-16 under 35 U.S.C. 101 have been fully considered but are not persuasive.
Applicant alleges that the claimed invention is patent eligible because it is not directed towards an abstract idea, specifically because the rejection presented above does not address the features of acquiring the “individual correlation information” and the “correlation trend indicator,” providing “price information,” and because the claimed invention is not directed towards a fundamental economic practice, e.g. see pgs. 9-10 of Remarks – Examiner disagrees.
As shown above, the steps of acquiring the individual correlation information and correlation trend indicator, and providing the price information have been addressed and recite offer-based price optimization, which is properly a fundamental economic practice – that is, the fundamental economic practice of optimizing a price. Furthermore, the aforementioned limitations are also directed towards managing personal behavior because they also recite following rules or instructions for performing price optimization. Furthermore, even assuming, arguendo, that the aforementioned limitations “define a specific relationship between multiple levels of derived data,” this does not preclude the data from reciting an abstract idea.
Additionally, even assuming, arguendo, that the claimed invention does recite a specific sequence using specific types of data for determining price information, Examiner notes that the Claims being narrowly claimed is not dispositive in determining the eligibility of the Claims. The Court has held that a claim may not preempt abstract ideas, laws of nature, or natural phenomena, even if the judicial exception is narrow, e.g. see MPEP 2106.04. That is, a claim reciting a narrow abstract idea nonetheless recites an abstract idea, and must be evaluated under the remainder of the requirements under 35 U.S.C. 101.
Applicant further alleges that the claimed invention is patent eligible because it recites an ordered combination that is not addressed by the grounds of rejection presented under 35 U.S.C. 101, specifically because the steps of acquiring the individual correlation information and correlation trend indicator, and determining the price information are not conventional, and hence amount to significantly more than the abstract idea, e.g. see pg. 10 of Remarks – Examiner disagrees.
Examiner initially notes that, as stated above, the steps of the acquiring the individual correlation information and correlation trend indicator, and determining the price information are considered part of the abstract idea rather than additional elements, and hence are not additional elements that could integrate the abstract idea into a practical application and/or amount to significantly more than the abstract idea.
Applicant also alleges that new Claim 16 is patent eligible because of the steps of using the sensitivity as an independent variable and the asking price as a dependent variable, determining the correlation trend indicator by a linear regression function, determining reliability of the survey data, and updating the determined price information, e.g. see pgs. 10-11 of Remarks – Examiner disagrees.
As stated above, new Claim 16 recites the limitations of Claim 1, but further incorporates limitations from dependent Claims 4-5, 7, and 10, which merely recite limitations further narrowing the abstract idea. That is, the aforementioned limitations recite functions that merely narrow the abstract idea and not any additional elements, and hence also do not integrate the abstract idea into a practical application and/or amount to significantly more than the abstract idea. Hence new Claim 16 is also rejected under the same rationale as presented above for Claims 1, 4-5, 7, and 10 under 35 U.S.C. 101.
For the aforementioned reasons, Claims 1-16 are rejected under 35 U.S.C. 101.
Applicant’s arguments, see Remarks, filed April 23, 2026, with respect to the rejections of Claims 1-16 under 35 U.S.C. 103 have been fully considered but are not persuasive.
Applicants allege that Gardner is deficient because it does not disclose an individual correlation of asking price relative to sensitivity in each of a plurality of surveys based on the survey data, does not disclose that the correlation trend indicator is based on a regression result of the individual correlation information, and further does not disclose providing the price information specifically based on the correlation trend indicator, e.g. see pgs. 12-13 of Remarks – Examiner disagrees.
Regarding the individual correlation information, as shown above, Gardner teaches analyzing customer survey data relative to the customer’s actions, wherein the customer may indicate that they are not influenced by price, but their actions show that they are indeed sensitive to price, e.g. see Gardner [0094] and [0139]-[0140]. Hence, Gardner teaches obtaining from a survey, a correlation between a price (i.e. an asking price) and the customer’s answers and/or actions (i.e. sensitivity). That is, given the broadest reasonable interpretation, the customer’s behavior in relation to the customer’s survey data and the price is properly interpreted as “individual correlation information.”
Regarding the correlation trend indicator being based on a regression result of the individual correlation information, Gardner teaches performing a regression analysis on the customer behavior (i.e. individual correlation information) and generating a model (i.e. the correlation trend indicator) that identifies a correlation between the customer behavior and successful outcomes in terms of acceptance by a provider, e.g. see Gardner [0094]-[0095]. Hence, Gardner teaches that the correlation trend indicator is based on a regression result of the individual correlation information.
Regarding the price information, Gardner teaches that the results presented to the user are determined by the model (i.e. the correlation trend indicator), e.g. see Gardner [0094] and [0112], Fig. 4d. Hence, Gardner teaches that the price information presented is determined based on the correlation trend indicator.
Hence Gardner is not deficient to teach the aforementioned features.
Furthermore, none of the other cited prior art references are cited to teach the aforementioned features, and hence the grounds of rejection presented in the Non-Final Rejection mailed on January 14, 2026 are maintained above.
Additionally, new Claim 16 recites the limitations of Claim 1, and further incorporates limitations from dependent Claims 4-5, 7, and 10. Hence, as shown above, the grounds of rejection for Claims 1, 4-5, 7, and 10 are combined to reject Claim 16 under 35 U.S.C. 103.
For the aforementioned reasons, Claims 1-16 are rejected under 35 U.S.C. 103.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN P GO whose telephone number is (703)756-1965. The examiner can normally be reached Monday-Friday 9am-6pm Pacific.
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/JOHN P GO/Primary Examiner, Art Unit 3681
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