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 .
DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following is a FIRST, NON-FINAL OFFICE ACTION for Application #18/045,619, filed on 10/11/2022.
Claims 1-20 are pending and have been examined.
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 1-4, 6-16, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The rationale for this finding is explained below.
Per Step 1 of the analysis, the claims are analyzed to determine if they are directed to statutory subject matter. Claim 1 claims a method, or process. A process is a statutory category for patentability. Claim 13 claims a computer system. The system comprises a memory and one or more processors. Therefore, the system is interpreted as an apparatus. An apparatus is a statutory category for patentability. Claim 20 claims a computer program product comprising one or more computer readable storage media. Paragraph [0015] of the filed specification clearly states that the media excludes transitory signals. Therefore, the media is interpreted as an article of manufacture, which is a statutory category for patentability. Further, the claim is in conformity with the Kappos Memorandum of 2010 regarding medium claims, as paragraph [0015] of the specification makes clear that the media include only non-transitory media.
Per Step 2A, Prong 1 of the analysis, the examiner must now determine if the claims recite an abstract idea or eligible subject matter. In the instant case, the independent claims are directed towards an abstract idea. Specifically, independent claims 1, 13, and 20 recite “determining…that a user has electronically purchased a product, classifying…the product into a product type classification, implementing…one or more trigger events, wherein based on each trigger event occurring…generate an inquiry to the user, wherein at least one of the one or more trigger events is implemented based on the product type classification, determining…that a trigger event of the one or more trigger events has occurred, based on the determining, generating…the inquiry to the user to solicit feedback on the product, obtaining…the feedback responsive to the inquiry, and generating…a product review based on the feedback obtained responsive to the inquiry.” Therefore, the claims recite an abstract idea, namely “certain methods of organizing human activity.” Specifically, the claims recite “marketing or sales activities, business relations.” A business owner could identify users who have purchase a product and classify their purchase, identify another trigger condition like being a new customer, and reach out to them for feedback and then publish or use the feedback. This is customary as part of running a business or marketing efforts. The claims simply automate these practices using a computer. Therefore, the claims recite an abstract idea. The claims are secondarily directed to a mental process. A business owner could identify users who have purchase a product and classify their purchase, identify another trigger condition like being a new customer, and reach out to them for feedback and then publish or use the feedback. These steps could all be done mentally with aid of pen and paper or other data files. The claims simply automate these practices using a computer. Therefore, the claims secondarily recite a mental process.
Per Step 2A, Prong 2 of the analysis, the examiner must now determine if the claims integrate the abstract idea into a practical application. The additional elements of the independent claims include “by one or more processors,” “one Internet of Things device,” “a memory,” and “a computer program product.” However, these additional elements are considered generic recitations of a technical element and are recited at a high level of generality. These additional elements are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and do not integrate the abstract idea into a practical application. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The additional elements “transmit an inquiry to the user.” While it is not included in the claims, the examiner is assuming this would be done over a network. Absent further detail, this additional element is considered “receiving and/or transmission of data over a network,” listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmittal of data over a network,” citing TLI Communications, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, this additional element is not considered to integrate the abstract idea into a practical application. The additional elements also include classifying “with at least one trained algorithm.” This additional element, absent further detail on how the algorithm is trained or the steps for using the algorithm, is considered a generic recitation of a technical element, the equivalent of “apply it,” or using a computer as a tool to automate the abstract idea. The computer is simply automating the abstract idea using an algorithm. Therefore, this additional element is not considered to integrate the abstract idea into a practical application.
Per Step 2B of the analysis, the examiner must now determine if the claims include limitations that are “significantly more” than the abstract idea by demonstrating an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The additional elements of the independent claims include “by one or more processors,” “one Internet of Things device,” “a memory,” and “a computer program product.” However, these additional elements are considered generic recitations of a technical element and are recited at a high level of generality. These additional elements are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and are not considered significantly more than the abstract idea itself. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The additional elements “transmit an inquiry to the user.” While it is not included in the claims, the examiner is assuming this would be done over a network. Absent further detail, this additional element is considered “receiving and/or transmission of data over a network,” listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmittal of data over a network,” citing TLI Communications, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, this additional element is not considered significantly more. The additional elements also include classifying “with at least one trained algorithm.” This additional element, absent further detail on how the algorithm is trained or the steps for using the algorithm, is considered a generic recitation of a technical element, the equivalent of “apply it,” or using a computer as a tool to automate the abstract idea. The computer is simply automating the abstract idea using an algorithm. Therefore, this additional element is not considered significantly more than the abstract idea itself.
When considered as an ordered combination, the claim is still considered to be directed to an abstract idea as the claim steps in the ordered combination simply recite the logical steps for determining a purchase, classifying the purchase, identifying a trigger condition, asking the user for feedback, and using the feedback to generate a review. Therefore, the ordered combination does not lead to a determination of significantly more.
When considering the dependent claims, claims 2-3 are considered part of the abstract idea. Claims 4 and 6 includes analyzing unstructured feedback using an NLP algorithm. This additional element is considered a generic recitation of a technical element, the equivalent of “apply it,” or using a computer as a tool to automate the abstract idea. Use of NLP is well known in the computer arts and there is no detail as to how it is used in the analysis other than “to isolate granular feedback….” Updating of the review is considered part of the abstract idea. The fact the text is found on a public product review site does not change the analysis. Claim 5 (and therefore 17) would be considered eligible subject matter if tied in with the independent claim and if the intervening claim 4 was also included. Claim 7 is considered part of the abstract idea, as the type of trigger event does not change the analysis. Claims 8 and 9, as written and absent further detail, are considered generic recitations of a technical element, the equivalent of “apply it,” or using a computer as a tool to automate the abstract idea. More detail to the monitoring similar to claim 5 and tied in to the analysis would potentially make the claims eligible pending further review. Claim 10 is considered part of the abstract idea, as the determining, updating, and generating steps are considered part of the marketing activity or mental process. Claim 11 is considered part of the abstract idea. Claim 12, as written and absent further detail as to how demographic information is obtained, is considered a generic recitation of a technical element, the equivalent of “apply it,” or using a computer as a tool to automate the abstract idea. More technical detail to how the demographics are determined would potentially make the claims eligible pending further review. The other dependent claims mirror those already discussed above.
Therefore, claims 1-4, 6-16, and 18-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. Vs. CLS Bank International et al., 2014 (please reference link to updated publicly available Alice memo at http://www.uspto.gov/patents/announce/alice_pec_25jun2014.pdf as well as the USPTO January 2019 Updated Patent Eligibility Guidance.)
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1, 11, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1.
Regarding Claims 1, 13, and 20, Fox teaches:
A computer-implemented method (system) (media)… comprising:
determining… that a user has electronically purchased a product (see [0013], [0019] in which a user is determined to have electronically purchase a product such as online)
implementing… one or more trigger events, wherein based on each trigger event occurring… automatically generate and transmit an inquiry to the user, wherein at least one of the one or more trigger events is implemented based on the product type classification (see [0021]-[0024] in which a trigger condition is an amount of product usage after a purchase and in response an inquiry for feedback to the user is initiated)
determining… that a trigger event of the one or more trigger events has occurred (see [0021]-[0024] in which a trigger event is a threshold amount of usage of the product)
based on the determining, generating… the inquiry to the user to solicit feedback on the product (see at least [0021]-[0024]
obtaining…the feedback responsive to the inquiry (see [0025])
generating…a product review based on the feedback obtained responsive to the inquiry (see [0016] and [0026] in which the user review feedback and other content is combined to generate a product review)
Fox, however, does not appear to specify:
classifying… with at least one trained algorithm, the product into a product type classification
Merkulov teaches:
classifying… with at least one trained algorithm, the product into a product type classification (see at least [0109]-[0111] in which trained machine learning models are used to classify the product into product types and categories)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Merkulov with Fox because Fox already teaches identification of purchased products and tracking of usage for the particular product and subsequent reviews eventually presented to other purchasers, and determination of a product type using an ML algorithm would allow for better determination of type which would lead to proper identification of what expected usage frequency and amount and energy use should be for that particular product type and allow for better presentation to other users.
Regarding Claim 11, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1
Fox further teaches:
determining…that a trigger event for delivery of the product review of the product has occurred and transmitting… the product review to the user (see [0015]-[0017] and [0024]-[0027] in which the generated product reviews are sent to users based on trigger events
Claims 2-3 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Anonymous IP.COM #IPCOM000258116D, 4/10/2019 (hereby Anonymous) (submitted by applicant on IDS).
Regarding Claims 2 and 14, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1…
Fox and Merkulov, however, does not appear to specify:
identifying…based on the product type classification, one or more components comprising the product, wherein the inquiry solicits granular information on at least a portion of the one or more components
Anonymous teaches:
identifying…based on the product type classification, one or more components comprising the product, wherein the inquiry solicits granular information on at least a portion of the one or more components (see page 2 in which the consumer uses one of the features of a product, and a survey is triggered to gather information from the consumer on the use of the product feature; examples are given to include “one or more features of a product being used by the consumer,” “is a part replacement is required,” and for such as an IoT dishwasher a sensor collects data such as type of cleaning mode to be used, type of payload selected for the activity, etc., and these are all considered to be associated with components of the product)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Anonymous with Fox and Merkulov because Fox already teaches in [0014] the products that a user is prompted for feedback for include such as home appliances, and consumer electronics, and identifying one or more components for which feedback is triggered would allow for better feedback on appliances and electronics which can have many different components that can affect overall experience and allows for other consumers to understand how a specific component affected the consumer experience.
Regarding Claims 3 and 15, the combination of Fox, Merkulov, and Anonymous teaches:
the computer-implemented method of claim 2…
Fox further teaches:
wherein the product review comprises the granular information (see [0016] and [0026] in which the generated product review includes consumer granular information about the product)
Claims 4-5, 7, 10-12, 16-17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Anonymous IP.COM #IPCOM000266381D, 4/10/2019 (hereby Anonymous 2) (submitted by applicant on IDS).
Regarding Claims 4 and 16, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1…
Fox and Merkulov, however, does not appear to specify:
obtaining…unstructured feedback relevant to the product
analyzing…the unstructured feedback via a natural language processing algorithm to isolate granular feedback pertaining to components comprising the product
updating… the product review based on the granular feedback
Anonymous 2 teaches:
obtaining…unstructured feedback relevant to the product (see page 4 #7 in which information is automatically collected on usage experience with the product using IoT devices)
analyzing…the unstructured feedback via a natural language processing algorithm to isolate granular feedback pertaining to components comprising the product (see at least page 4 #8 in which the feedback is analyzed using NLP techniques; see also such as page 2 in which a hotspot of a phone is the component; see also page 6 which includes the toner of the printer)
updating… the product review based on the granular feedback (see page 4 #’s 9-11 in which the review is updated prior to publishing based on the NLP analysis and other inputs)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Anonymous 2 with Fox and Merkulov because Fox already teaches in [0014] the products that a user is prompted for feedback for include such as home appliances, and consumer electronics, and the feedback is used to generate reviews, and also monitors the user activity and then prompts the user for feedback, and using NLP to refine unstructured feedback would allow for feedback from IoT and other devices to be used in generating the review, allowing for other sources of feedback to be relevant rather than relying only on user input.
Regarding Claims 5 and 17, the combination of Fox, Merkulov, and Anonymous 2 teaches:
the computer-implemented method of claim 4…
Anonymous 2 further teaches:
wherein obtaining the unstructured feedback comprises:
controlling…at least one Internet of Things device to monitor an area proximate to the product, wherein the unstructured feedback comprises audio data collected by the at least one Internet of Things device (see page 4 #7 in which the IoT device sensors and cameras are used to monitor the consumer living space with the products and collect unstructured feedback)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Anonymous 2 with Fox and Merkulov because Fox already teaches energy and activity monitors installed in the consumer home to monitor specific products, and using IoT devices would allow for other types of feedback including audio and visual which would lead to better overall understanding of the user experience.
Regarding Claims 7 and 19, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1…
Fox and Merkulov, however, does not appear to specify:
wherein each event of the one or more trigger events is selected from the group consisting of: taking delivery of the product, purchasing a similar product, requesting a repair for the product, and utilizing the product in a manner outside an established pattern of use
Anonymous 2 teaches:
wherein each event of the one or more trigger events is selected from the group consisting of: taking delivery of the product, purchasing a similar product, requesting a repair for the product, and utilizing the product in a manner outside an established pattern of use (see page 2 in which trigger events are an issue with a hotspot or an issue with delivery and installation, page 3 which includes technical issues, page 4 which includes delays in shipping, product damage; see also page 6 in which the toner component having issues is the trigger event, and page 7 in which the feedback includes repair support for the product)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Anonymous 2 with Fox and Merkulov because Fox already teaches other trigger events such as amount of usage or review of another product, and these trigger events allow for more service related issues such as repairs, delivery, and technical issues to be addressed as well.
Regarding Claim 10, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1
Fox further teaches:
based on determining that there is no existing review, generating the product review based on the feedback obtained responsive to the inquiry (see such as [0015]-[0016] and [0024]-[0027])
Fox and Merkulov, however, does not appear to specify:
wherein generating the product review based on the feedback obtained responsive to the inquiry further comprises:
determining…if there is an existing product review for the product
based on determining that there is an existing product review for the product, updating… the existing review to generate the product review
Anonymous 2 teaches:
wherein generating the product review based on the feedback obtained responsive to the inquiry further comprises:
determining…if there is an existing product review for the product and based on determining that there is an existing product review for the product, updating… the existing review to generate the product review (see pages 4 and 6-8 in which the user has submitted a review and the review is then updated or edited)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Anonymous 2 with Fox and Merkulov because Fox already teaches generation of reviews based on collected consumer feedback and other information, and updating and already submitted review allows for an easier consumer experience, making it more likely for them to participate if the review can simply be updated instead of a new one being submitted.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Roy, et al., Pre-Grant Publication No. 2021/0241289 A1.
Regarding Claim 8, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1
Fox and Merkulov, however, does not appear to specify:
wherein determining that a trigger event of the one or more trigger events has occurred comprises:
controlling…at least one Internet of Things device to monitor an area proximate to the product
based on the monitoring, generating…a baseline model representing a usage pattern of the product by the user
identifying… at least one outlier to the baseline model
Roy teaches:
wherein determining that a trigger event of the one or more trigger events has occurred comprises:
controlling…at least one Internet of Things device to monitor an area proximate to the product (see [0038]-[0041] and [0049]-[0053] in which IoT devices monitor usage of products by consumers in their home)
based on the monitoring, generating…a baseline model representing a usage pattern of the product by the user (see [0038]-[0041] and [0049]-[0053] in which based on the monitoring, trained models are used to establish a usage pattern based model of usage)
identifying… at least one outlier to the baseline model (see [0058]-[0060] in which a change in the usage behavior from the identified pattern occurs, which would be considered an “outlier” as claimed)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Roy with Fox and Merkulov because Fox already teaches trigger events involving sensors monitoring usage amounts, and establishing baseline usage patterns and outliers allows for a more accurate determination of a trigger event based on more direct and individualized measurement versus partial inference based on other factors or only a threshold, which can be more accurate for some consumers than others.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Official Notice.
Regarding Claim 9, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 1
Fox and Merkulov, however, does not appear to specify:
wherein determining that a trigger event of the one or more trigger events has occurred comprises:
controlling…at least one Internet of Things device to monitor an area proximate to the product
based on the monitoring, determining… that the user has not utilized the product within a pre-configured time window for usage of the product
The examiner, however, takes Official Notice that it is old and well known in the commerce arts to monitor product usage and identify a threshold amount of time in which an action has or has not taken place and use those as trigger events to communicate with a user or make suggestions and take other actions. Companies such as Amazon.com, Verizon, American Express, and others have done so for many years prior to the effective filing date of the application.
Therefore, it would be obvious to one of ordinary skill in the art to combine controlling…at least one Internet of Things device to monitor an area proximate to the product and based on the monitoring, determining… that the user has not utilized the product within a pre-configured time window for usage of the product with Fox and Merkulov because Fox already teaches trigger events involving sensors monitoring usage amounts and communicating with a user accordingly, and determining a product has not been used would allow for determination of communication with the user based on that trigger event.
Claims 6 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Anonymous IP.COM #IPCOM000266381D, 4/10/2019 (hereby Anonymous 2) (submitted by applicant on IDS) and in further view of Official Notice.
Regarding Claims 6 and 18, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 4…
Fox and Merkulov, however, does not appear to specify:
wherein obtaining the unstructured feedback comprises:
identifying…on one or more public product review sites, text relevant to the product, wherein the unstructured feedback comprises the text
The examiner, however, takes Official Notice that it is old and well known in the commerce arts to monitor, scrape, and use as an information source public sites such as websites for data such as text including such as reviews, comments, and opinions. Companies such as Amazon.com, Google, and others have done so for at least a decade prior to the effective filing date of the application.
Therefore, it would be obvious to one of ordinary skill in the art to combine identifying…on one or more public product review sites, text relevant to the product, wherein the unstructured feedback comprises the text with Fox and Merkulov because Fox already teaches gathering unstructured feedback regarding reviews, and using public sites would allow for a larger scale of current and verified reviews to be used, allowing the system to put forward more accurate information.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Fox, et al., Pre-Grant Publication No. 2019/0378178 A1 in view of Merkulov, et al., Pre-Grant Publication No. 2023/0252544 A1 and in further view of Fox, et al., Pre-Grant Publication No. 2021/0103971 A1 (hereby Fox 2) and in further view of Balasubramanian, et al., Pre-Grant Publication No. 2019/0205950 A1 (hereby Bala).
Regarding Claim 12, the combination of Fox and Merkulov teaches:
the computer-implemented method of claim 11
Fox and Merkulov, however, does not appear to specify:
obtaining… from one or more Internet of Things devices proximate to the user, demographic information related to the user
Fox 2 teaches:
obtaining… from one or more Internet of Things devices proximate to the user, demographic information related to the user (see [0031] in which the IoT device collects demographic information for customer analysis)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Fox 2 with Fox and Merkulov because Fox already teaches monitoring of user activity and gathering other user information through sensors, and using IoT devices to gather demographic information would allow for more robust information for various targeting purposes.
Fox and Merkulov and Fox 2, however, does not appear to specify:
filtering… the product review based on the demographic information
transmitting… the filtered review to the user
Bala teaches:
filtering… the product review based on the demographic information and transmitting… the filtered review to the user (see Abstract, Figures 6A-6E, and [0027] in which product reviews are filtered by demographics and reviews transmitted to another user can be filtered by demographics)
It would have been obvious to one of ordinary skill in the art at the time of the filing of the application to combine Fox with Fox, Merkulov, and Fox 2 because Fox already teaches monitoring of user activity and gathering other user information through sensors, and Fox 2 already teaches an IoT device to gather demographic information, and filtering by demographics would give the user a more demographic relevant set of reviews, which can be important with specific products and accompanying reviews, such as for age and gender.
Conclusion
The following prior art references were not relied upon in this office action but are considered pertinent to the applicant’s invention:
DeLuca, et al., Pre-Grant Publication No. 2019/0087874 A1- teaches IoT sensors to detect user product activity after purchase as well as prompting users for reviews and generating reviews.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Luis A. Brown whose telephone number is 571.270.1394. The Examiner can normally be reached on Monday-Friday 8:30am-5:00pm EST. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, JESSICA LEMIEUX can be reached at 571.270.3445.
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/LUIS A BROWN/Primary Examiner, Art Unit 3626