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 .
Status of Claims
This office action is in response to the election without traverse of claims 10-20 filed on 3/12/2026.
Claims 1-9 are now withdrawn.
Claims 10-20 are pending and have been examined.
Election/Restrictions
Applicant’s election without traverse of claims 10-20 in the reply filed on 3/12/2026 is acknowledged.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2022-0093437, filed on 7/27/2022.
Claim Objections
Claim 11 is objected to because of the following informalities: Claim 11 recites: “wherein the at least one processor is configured to identified a plurality of weight values…” “Identified” is grammatically incorrect. The examiner recommends changing “identified” to “identify.” Appropriate correction is required.
Claim 16 is objected to because of the following informalities: Claim 16 recites “The electronic device according to Claim 10, Wherein, if the first celebrity image…” “Wherein” should not be capitalized. The examiner recommends amending “Wherein” to “wherein.” Appropriate correction is required.
Claim 17 recites “determine the predetermined number of weight values…” In accordance with specification paragraph [90], it is clear that this is merely a typo that should be “a” instead of “the.” The examiner recommends changing “the” to “a.” Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “celebrity” in claims 10-16, 18, and 20 is a relative term which renders the claim indefinite. The term “celebrity” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. What would be considered a celebrity to one person may not be considered a celebrity to another. The claim does not define what applicant means by celebrity. Further, the specification, as best the examiner can infer, seems to imply simply that a celebrity is a famous person (spec [9], [10]). However, famous is also a relative term, and thus does not confer a boundary for the term. The examiner recommends replacing celebrity with a term that is simply referring to a person. Some possible suggestions include endorser, brand representative, spokesperson, brand ambassador, or the like. The remaining claims are rejected as each depends from claim 10.
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 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 10-19 are directed to a device. Claim 20 is directed to a method. Thus, on their face they fall within the four statutory categories of patentable subject matter.
Step 2A prong 1:
Claims 10 and 20 recite virtually identical claim language. Claim 20 will be used as representative. Each claims additional elements will be addressed individually. The following limitations, when considered individually and as an ordered combination, are merely descriptive of abstract concepts:
Claims 10, 20:
obtaining at least one content of a specific product, wherein the at least one content including an image of the specific product;
obtaining product attribute information of the specific product based on the at least one content, wherein the product attribute information is corresponding to a plurality of product features;
obtaining a plurality of celebrity features for each of a plurality of celebrity images based on the plurality of celebrity images, wherein the plurality of celebrity features for each celebrity image includes first features for a first image of a specific celebrity and second features for a second image of the specific celebrity, and the first features and the second features are at least partially different;
obtaining at least one celebrity image among the plurality of celebrity images and a predetermined celebrity feature among a plurality of features corresponding to the at least one celebrity image, based on the product attribute information;
obtaining celebrity image recommendation information including the at least one celebrity image and the predetermined celebrity features; and
displaying a first display including the at least one celebrity image and the predetermined celebrity features based on the celebrity image recommendation information.
The following dependent claim limitations, when considered individually and as an ordered combination, are merely further descriptive of abstract concepts:
Claim 11: identified a plurality of weight values corresponding to each of the plurality of product features based on the product attribute information, and wherein the at least one celebrity image and the predetermined celebrity features corresponding to the at least one celebrity image are obtained based on the plurality of weight values.
Claim 12: wherein the predetermined celebrity features correspond to the predetermined number of weight values among the plurality of weight values.
Claim 13: wherein the first display includes celebrity feature values corresponding to the predetermined celebrity features for each of the at least one celebrity image.
Claim 14: wherein the first display further includes at least one other celebrity image of a celebrity of each celebrity image included in the celebrity image recommendation information.
Claim 15: provide a mediation interface with the first celebrity of a first celebrity image, if the first celebrity image among the at least one celebrity image displayed on the first display is selected.
Claim 16: Wherein, if the first celebrity image among the at least one celebrity image displayed on the first display is selected, display a second display providing an image of the specific product, the selected first celebrity image, and an advertisement image generated based on the image of the specific product and the selected first celebrity image
Claim 17: compare sizes of the plurality of weight values, and determine the predetermined number of weight values among the plurality of weight values with larger sizes based on the result of the comparison.
Claim 18: identify celebrity attribute information of a plurality of celebrity images,
perform calculations on the plurality of weight values and the identified celebrity attribute information, and
identify the at least one celebrity image based on the result of the calculations.
Claim 19: wherein the plurality of weight values are: identified, based on the specific product being a first product, based on a reference matrix and first product attribute information of the first specific product, and identified, based on the specific product being a second product, based on the reference matrix and second product attribute information of the second specific product; and wherein the first product attribute information and the second product attribute information are at least partially different.
The claims provide a manner of obtaining images of a product, images of celebrities, obtaining attributes of the product and features of the celebrities form the images, and recommending a celebrity image based on the product attributes and celebrity features for the purpose of creating advertisements (spec [1], [4], [5]). Thus, when considered individually and as an ordered combination, the claims embody certain methods of organizing human activity. Specifically, such activity is in the form of commercial interactions (in the form of advertising, marketing or sales activities or behaviors).
Additionally, but for the inclusion of generic computing devices, a human analog would be able to obtain an image of a product, obtain product attributes from the image, obtain a plurality of celebrity features for a plurality of celebrity images, match celebrity features to the product attributes to obtain a celebrity image, and recommend the celebrity image. Thus, the claims fall under the mental process grouping of abstract ideas.
Step 2A prong 2: This judicial exception is not integrated into a practical application. The claims recite the following additional elements: first screen (claims 10, 13-16, 20); electronic device comprising a display, a memory, and at least one processor (claim 10, 11, 15, 16, 17, 18); second screen (claim 16);
The electronic device comprising a display, a memory, and at least one processor is recited at a high level of generality and amount to “apply it” (the abstract idea) using generic computing devices (spec [35], [172]). The computer merely sends and receives data (obtains, provide), processes data (identify, determine, perform calculations), and provides generic displaying (display). Nothing in the claims improves upon computers themselves, technology, or a technical field (See MPEP 2106.05(f)).
The first and second screens merely provide a general link to a particular technological environment (i.e. on a computer). This is merely a digital display medium as opposed to paper or any other medium. Nothing in the claims improves upon screen technology or a technical field (See MPEP 2106.05(h))
Accordingly, when considered both individually and as an ordered combination, the additional elements do not impose any meaningful limits on practicing the abstract idea.
Step 2B: The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Similarly, as above with regard to practical application, the additional elements when considered both individually and as an ordered combination, do not provide an inventive concept as they merely provide generic computing components used as a tool to implement the abstract idea and provide a general link to a particular technological environment or field of use (i.e. online).
As a result, the claims are not patent eligible.
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) 10-16, 18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hewitt et al (US 2020/0111129) in view of Chopra et al (US 2021/0073267) in view of Saxena et al (US 11,245,966) in view of Singh (US 2016/0125473)
Claims 10 and 20 recite virtually identical limitations. Limitations unique to each claim will be addressed individually and limitations common to both will be addressed together.
As per claims 10 and 20:
Hewitt teaches:
Claim 10: An electronic device comprising: a display; a memory; and at least one processor, wherein the at least one processor is configured to ([0025]):
Claim 20: A method of operating an electronic device, the method comprising ([0017]):
Claims 10 and 20:
obtain product attribute information of the specific product based on the at least one content, wherein the product attribute information is based on a plurality of product features; ([0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0059] FIG. 6 is an exemplary high-level flowchart showing steps taken to select designated agents to promote a business' product or service. FIG. 6 processing commences at 600 whereupon, at step 610, the process captures branding characteristics (business characteristics) pertaining to the business' brand, such as their type of product/service, their overall business brand attributes (wholesome, edgy, reliable, etc.). At step 620, the process identifies preferred user traits corresponding to the branding characteristics (e.g., clean cut, long hair, tall, etc.).)
obtain a plurality of celebrity features for each of a plurality of celebrity images based on the plurality of celebrity images, wherein the plurality of celebrity features for each celebrity image includes first features for a first image of a specific celebrity and second features for a second image of the specific celebrity, ([0032] In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0047] Next, agent management engine 300 determines an optimal collection of users to represent business 310 using approaches such as: [0048] Determine individuals with number of followers that match business 310's predetermined threshold of interest [0049] Via image processing or text processing (depending on whether images or texts that are being reviewed), determine with level of confidence the types of images and posts the user often shares [0050] Scan images to determine the images' constituent parts while building a class mode to collect the elements of each image. [0051] Via sentiment/tone analysis, analyze the number of likes on a category of images that are deemed prominent to a user's profile and correlate those with comments associated with posts to determine whether the content is being positively or negatively received by the network. [0052] Combine the class model with a timeliness of emotive feedback to infer which image elements or post topics are currently trending in which social cohorts. [0053] Aggregate the respective information to determine with some level of confidence the best likely candidates to share with businesses to represent their product, brand, service, etc.)
obtain {…} and a predetermined celebrity feature among a plurality of features corresponding to the at least one celebrity image, based on the product attribute information; ([0032] In one embodiment, the information handling system accurately identifies traits to the user's popularity and correlates the traits with the appropriate product, services, etc., to find the right business to alert for advertisement potential. In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0061] At step 650, the process selects the first potential agent and, at predefined process 660, the process evaluates the potential agent against business characteristics and assigns candidate scores accordingly to rank the potential agents (see FIG. 7 and corresponding text for processing details). The process determines as to whether there are more potential agents to evaluate (decision 670). If there are more potential agents, then decision 670 branches to the ‘yes’ branch which loops back to select and evaluate the next potential agent. This looping continues until there are no more potential agents to evaluate, at which point decision 670 branches to the ‘no’ branch exiting the loop. The {…} indicates a modification to the claim language to show what is expressly taught by the reference. The limitations not addressed by the reference will be addressed below.)
obtain celebrity image recommendation information including {…} the predetermined celebrity feature; and ([0032] In one embodiment, the information handling system accurately identifies traits to the user's popularity and correlates the traits with the appropriate product, services, etc., to find the right business to alert for advertisement potential. In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0057] Agent management engine 300 also provides agent statistics 440 to business 310, which may include a list of the top five designated agents receiving positive feedback from promoting business 310's products/services. Agent management engine 300 also provides threshold recommendations 450 based on the analysis. In one embodiment, threshold recommendations 450 are customized by users or automatically detected and sent by agent management engine 300. In this embodiment, threshold recommendations 450 are based on the priority and interest of business 310 and are also specific to the designated agent. The {…} indicates a modification to the claim language to show what is expressly taught by the reference. The limitations not addressed by the reference will be addressed below.)
Hewitt does not expressly teach obtain at least one content of a specific product, wherein the at least one content including an image of the specific product.
Chopra teaches:
obtain at least one content of a specific product, wherein the at least one content including an image of the specific product; ([0023] This disclosure describes one or more embodiments of a cognitive attribute classification system that intelligently trains and applies a cognitive attribution neural network to identify digital attributes from multiple attribute groups within target digital images. In particular, the cognitive attribute classification system can utilize a cognitive attribution neural network that includes a base neural network and one or more attribute group classifiers to determine tags for objects portrayed in query images. For instance, the cognitive attribute classification system can use a base neural network that includes an architecture of interleaved layers to efficiently localize attributes of a query image. [0032] Further, as used herein, the term “attribute” refers to one or more properties, features, and/or characteristics of a digital image and/or item. In particular, an attribute can define one or more aspects of an object portrayed in a query image. Additionally, the term “attribute group” as used herein refers to a category, class, or type of attributes. In particular, an attribute group can include a category of attributes that describes or encompasses a plurality of attributes. For example, an attribute group can include a sleeve type, and attributes within the attribute group of sleeve type can include three-quarter sleeve, spaghetti, sleeveless, elbow, extra long, extra short, long short, strapless, etc. [0052] As mentioned above, the cognitive attribute classification system 106 can generate tags based on attributes of an object portrayed in a digital image. FIG. 2 illustrates a schematic diagram of the cognitive attribute classification system 106 generating tags 210 associated with a query 202, in accordance with one or more embodiments of the present disclosure. As shown, the cognitive attribute classification system 106 utilizes a cognitive attribution neural network 208 that receives the query 202 as an input and generates the tags 210 as a corresponding output. [0055] For example, with regard to an example digital image that portrays a shirt, the attribute group classifier 206a can predict attributes of the example attribute group of gender (e.g., male or female); the attribute group classifier 206b can predict attributes of the example attribute group of collar type (e.g., straight point, semi spread, cutaway, spread, etc.); another attribute group classifier can predict attributes of the example attribute group of sleeve type (e.g., long sleeve, elbow sleeve, short sleeve, tank top, etc.); yet another attribute group classifier can predict attributes of the example attribute group of pocket type; still another attribute group classifier can predict attributes of the example attribute group of texture type; another attribute group classifier can predict attributes of the example attribute group of neckline type (e.g., v-neck, crew, scoop, etc.); and so forth.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include obtain at least one content of a specific product, wherein the at least one content including an image of the specific product as taught by Chopra with the matching of products to potential endorsers of Hewiit in order to reduce inefficiencies in time, resources, user interfaces, and user interactions in scrolling through search results to identify pertinent digital content ([0005]).
Hewitt in view of Chopra does not expressly teach {obtain} at least one celebrity image among the plurality of celebrity images, {obtain recommendation information including} the at least one celebrity image, {obtain} at least one celebrity image among the plurality of celebrity images and display, on the display, a first screen including the at least one celebrity image and the predetermined celebrity feature based on the celebrity image recommendation information.
Saxena teaches:
{obtain} at least one celebrity image among the plurality of celebrity images ([C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
{obtain recommendation information including} the at least one celebrity image and {obtain} at least one celebrity image among the plurality of celebrity images ([C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
display, on the display, a first screen including the at least one celebrity image and the predetermined celebrity feature based on the celebrity image recommendation information. ([C30L61-C31L20] As further shown in FIG. 5B, the insight interface 508 includes sample user-generated digital content items 512 in which the identified combination of products is shown. For example, in one or more embodiments, the networking system 104 identifies sample user-generated digital content items 512 shared by various users of the networking system 104 and provides, within the insight interface 508, any number of the sample identified user-generated digital content items 512 for display within the system interface 206. Thus, a user of the mobile device (e.g., merchant, influencer, end-user) can view one or more example posts from various users of the networking system 104 in which the identified combination of products are shown. Moreover, in one or more embodiments, the networking system 104 includes a combination of products shown within the plurality of posts 506 shared by the user of the mobile device 202. For example, in one or more embodiments, each of the first product 510a and the second product 510b refer to products provided within one or more of the 4,112 posts by an administrative user of the account for Palm Clothing. [C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include {obtain} at least one celebrity image among the plurality of celebrity images, {obtain recommendation information including} the at least one celebrity image, {obtain} at least one celebrity image among the plurality of celebrity images and display, on the display, a first screen including the at least one celebrity image and the predetermined celebrity feature based on the celebrity image recommendation information as taught by Saxena with the matching of products to potential endorsers of Hewiit in view of Chopra in order to provide an effective way for viewers of digital media to learn more information about products shown within digital media ([C1L47-49]).
Hewiit in view of Chopra in view of Saxena does not expressly teach the first features and the second features are at least partially different.
Singh teaches:
the first features and the second features are at least partially different; [0021] For example, the advertisement application 212 may analyze a first image of a user, and determine that the user has 10% body fat, has black hair, and healthy skin. The advertisement application 212 may then store indications (or values) to reflect these attributes in the user's profile in the profiles 209. [0023] At step 320, the advertisement application 212 may extract physical attributes from the image, and store the extracted physical attributes in the profiles 209. For example, the advertisement application 212 may determine that the user has wrinkled skin, is showing signs of baldness, and has an estimated 15% body fat percentage. The advertisement application 212 may then store these attributes in the profiles 209. [0024] At step 330, the advertisement application 212 may receive a second image of the customer at a later time. At step 340, the advertisement application 212 may extract physical attributes from the second image, and store the extracted attributes in the profiles 209. For example, the advertisement application 212 may extract attributes from the December 6.sup.th photo indicating the customer has lost even more hair, has healthier skin, and now has an estimated body fat percentage of 10%.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the first features and the second features are at least partially different as taught by Singh with the matching of products to potential endorsers of Hewiit in view of Chopra in view Saxena in order to compare changes in the person (paragraph [0003]).
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 10. As per claim 11:
Hewitt further teaches:
wherein the at least one processor is configured to identified a plurality of weight values corresponding to each of the plurality of product features based on the product attribute information, and wherein the at least one celebrity image and the predetermined celebrity features corresponding to the at least one celebrity image are obtained based on the plurality of weight values. ([0032] In one embodiment, the information handling system accurately identifies traits to the user's popularity and correlates the traits with the appropriate product, services, etc., to find the right business to alert for advertisement potential. In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0036] Additionally, agent management engine 300 allows advertisers the flexibility to decide what they are and are not interested in and to what extent certain parameters must match the desired criteria. Examiner’s Comment: When selecting criteria and overlooking other criteria, the criteria is interpreted as weighted, as the inclusion of a variable gives it a weight of 1 and variables that been excluded have a weight of 0.)
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 11. As per claim 12:
Hewitt further teaches:
wherein the predetermined celebrity features correspond to the predetermined number of weight values among the plurality of weight values. ([0032] In one embodiment, the information handling system accurately identifies traits to the user's popularity and correlates the traits with the appropriate product, services, etc., to find the right business to alert for advertisement potential. In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0036] Additionally, agent management engine 300 allows advertisers the flexibility to decide what they are and are not interested in and to what extent certain parameters must match the desired criteria. Examiner’s Comment: When selecting criteria and overlooking other criteria, the criteria is interpreted as weighted, as the inclusion of a variable gives it a weight of 1 and variables that been excluded have a weight of 0.)
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 10. As per claim 13:
Hewiit in view of Chopra in view of Singh does not expressly teach wherein the first screen includes celebrity feature values corresponding to the predetermined celebrity features for each of the eat least one celebrity image.
Saxena teaches:
wherein the first screen includes celebrity feature values corresponding to the predetermined celebrity features for each of the eat least one celebrity image ([C30L61-C31L20] As further shown in FIG. 5B, the insight interface 508 includes sample user-generated digital content items 512 in which the identified combination of products is shown. For example, in one or more embodiments, the networking system 104 identifies sample user-generated digital content items 512 shared by various users of the networking system 104 and provides, within the insight interface 508, any number of the sample identified user-generated digital content items 512 for display within the system interface 206. Thus, a user of the mobile device (e.g., merchant, influencer, end-user) can view one or more example posts from various users of the networking system 104 in which the identified combination of products are shown. Moreover, in one or more embodiments, the networking system 104 includes a combination of products shown within the plurality of posts 506 shared by the user of the mobile device 202. For example, in one or more embodiments, each of the first product 510a and the second product 510b refer to products provided within one or more of the 4,112 posts by an administrative user of the account for Palm Clothing. [C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include wherein the first screen includes celebrity feature values corresponding to the predetermined celebrity features for each of the eat least one celebrity image as taught by Saxena with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Singh in order to provide an effective way for viewers of digital media to learn more information about products shown within digital media ([C1L47-49]).
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 10. As per claim 14:
Hewiit in view of Chopra in view of Singh does not expressly teach wherein the first screen further includes at least one other celebrity image of a celebrity of each celebrity image included in the celebrity image recommendation information.
Saxena teaches:
wherein the first screen further includes at least one other celebrity image of a celebrity of each celebrity image included in the celebrity image recommendation information ([C30L61-C31L20] As further shown in FIG. 5B, the insight interface 508 includes sample user-generated digital content items 512 in which the identified combination of products is shown. For example, in one or more embodiments, the networking system 104 identifies sample user-generated digital content items 512 shared by various users of the networking system 104 and provides, within the insight interface 508, any number of the sample identified user-generated digital content items 512 for display within the system interface 206. Thus, a user of the mobile device (e.g., merchant, influencer, end-user) can view one or more example posts from various users of the networking system 104 in which the identified combination of products are shown. Moreover, in one or more embodiments, the networking system 104 includes a combination of products shown within the plurality of posts 506 shared by the user of the mobile device 202. For example, in one or more embodiments, each of the first product 510a and the second product 510b refer to products provided within one or more of the 4,112 posts by an administrative user of the account for Palm Clothing. [C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include wherein the first screen further includes at least one other celebrity image of a celebrity of each celebrity image included in the celebrity image recommendation information as taught by Saxena with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Singh in order to provide an effective way for viewers of digital media to learn more information about products shown within digital media ([C1L47-49]).
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 10. As per claim 15:
Hewitt further teaches:
wherein the at least one processor is configured to provide a mediation interface with the first celebrity of a first celebrity image, if the first celebrity image among the at least one
celebrity image displayed on the first screen is selected. ([0054] Agent management engine 300 then shares the optimal collection of users (candidate agents 360) with business 310. Business 310, in turn, provides agent selection 370 to agent management engine 300 and agent management engine 300 sends requests to the selected agents (agent requests 380) asking whether they are interested in being designated agents of business 310. Agent management engine 300 receives agent responses 390 from users 340 indicating acceptance/rejection. In turn, agent management engine 300 assigns a set of designated agents to business 310 and monitors their activity accordingly (see FIG. 4 and corresponding text for further details).)
Hewiit in view of Chopra in view Saxena in view of Singh teach the limitations of claim 10. As per claim 16:
Hewiit in view of Chopra in view of Singh does not expressly teach wherein, if the first celebrity image among the at least one celebrity image displayed on the first screen is selected, the at least one processor is configured to display a second screen providing an image of the specific product, the selected first celebrity image, and an advertisement image generated based on the image of the specific product and the selected first celebrity image.
Saxena further teaches:
wherein, if the first celebrity image among the at least one celebrity image displayed on the first screen is selected, the at least one processor is configured to display a second screen providing an image of the specific product, the selected first celebrity image, and an advertisement image generated based on the image of the specific product and the selected first celebrity image ([C30L61-C31L20] As further shown in FIG. 5B, the insight interface 508 includes sample user-generated digital content items 512 in which the identified combination of products is shown. For example, in one or more embodiments, the networking system 104 identifies sample user-generated digital content items 512 shared by various users of the networking system 104 and provides, within the insight interface 508, any number of the sample identified user-generated digital content items 512 for display within the system interface 206. Thus, a user of the mobile device (e.g., merchant, influencer, end-user) can view one or more example posts from various users of the networking system 104 in which the identified combination of products are shown. Moreover, in one or more embodiments, the networking system 104 includes a combination of products shown within the plurality of posts 506 shared by the user of the mobile device 202. For example, in one or more embodiments, each of the first product 510a and the second product 510b refer to products provided within one or more of the 4,112 posts by an administrative user of the account for Palm Clothing. [C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include wherein, if the first celebrity image among the at least one celebrity image displayed on the first screen is selected, the at least one processor is configured to display a second screen providing an image of the specific product, the selected first celebrity image, and an advertisement image generated based on the image of the specific product and the selected first celebrity image as taught by Saxena with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Singh in order to provide an effective way for viewers of digital media to learn more information about products shown within digital media ([C1L47-49]).
Hewitt in view of Chopra in view of Saxena in view of Singh teaches the limitations of claim 11. As per claim 18:
Hewitt further teaches:
wherein the at least one processor is configured to: identify celebrity attribute information of a plurality of celebrity images, ([0032] In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0047] Next, agent management engine 300 determines an optimal collection of users to represent business 310 using approaches such as: [0048] Determine individuals with number of followers that match business 310's predetermined threshold of interest [0049] Via image processing or text processing (depending on whether images or texts that are being reviewed), determine with level of confidence the types of images and posts the user often shares [0050] Scan images to determine the images' constituent parts while building a class mode to collect the elements of each image. [0051] Via sentiment/tone analysis, analyze the number of likes on a category of images that are deemed prominent to a user's profile and correlate those with comments associated with posts to determine whether the content is being positively or negatively received by the network. [0052] Combine the class model with a timeliness of emotive feedback to infer which image elements or post topics are currently trending in which social cohorts. [0053] Aggregate the respective information to determine with some level of confidence the best likely candidates to share with businesses to represent their product, brand, service, etc.)
perform calculations on the plurality of weight values and the identified celebrity attribute information, ([0032] In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0047] Next, agent management engine 300 determines an optimal collection of users to represent business 310 using approaches such as: [0048] Determine individuals with number of followers that match business 310's predetermined threshold of interest [0049] Via image processing or text processing (depending on whether images or texts that are being reviewed), determine with level of confidence the types of images and posts the user often shares [0050] Scan images to determine the images' constituent parts while building a class mode to collect the elements of each image. [0051] Via sentiment/tone analysis, analyze the number of likes on a category of images that are deemed prominent to a user's profile and correlate those with comments associated with posts to determine whether the content is being positively or negatively received by the network. [0052] Combine the class model with a timeliness of emotive feedback to infer which image elements or post topics are currently trending in which social cohorts. [0053] Aggregate the respective information to determine with some level of confidence the best likely candidates to share with businesses to represent their product, brand, service, etc.)
Hewitt in view of Chopra in view of Singh does not expressly teach identify the at least one celebrity image based on the result of the calculations.
Saxena teaches:
and identify the at least one celebrity image based on the result of the calculations. ([C31L47-62] In addition or as an alternative to providing a creation insight including an identification of one or multiple products, the networking system 104 can additionally search a database associated with a respective user and identify one or more digital content items (e.g., user-generated digital content items) to recommend to the user for a subsequent post. For example, in one or more embodiments, the networking system 104 searches a local storage (e.g., a camera roll) of a client device and determines engagement scores for images (or other user-generated digital content items) within the local storage that predict user-engagement with the images of the local storage. The networking system 104 can further generate a creation insight including an identification of one or more images from the local storage based on the associated engagement scores (e.g., having the highest engagement scores).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include identify the at least one celebrity image based on the result of the calculations as taught by Saxena with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Singh in order to provide an effective way for viewers of digital media to learn more information about products shown within digital media ([C1L47-49]).
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hewitt et al (US 2020/0111129) in view of Chopra et al (US 2021/0073267) in view of Saxena et al (US 11,245,966) in view of Singh (US 2016/0125473) in view of Collins (US 8,458,072)
Hewitt in view of Chopra in view of Saxena in view of Singh teaches the limitations of claim 11. As per claim 17:
Hewitt in view of Chopra in view of Saxena in view of Singh does not expressly teach wherein the at least one processor is configured to: compare sizes of the plurality of weight values, and determine the predetermined number of weight values among the plurality of weight values with larger sizes based on the result of the comparison.
Collins teaches:
wherein the at least one processor is configured to: compare sizes of the plurality of weight values, and determine the predetermined number of weight values among the plurality of weight values with larger sizes based on the result of the comparison. ([C4L50-57] In a preferred embodiment of the invention, weights for each variable may be adjusted for various factors. In an embodiment of the invention, variables with the highest weight are preferably those defined to be closely correlated to the profile characterizes the product and/or service. Processing component 206 compares the weight for each variable with data extracted from the external sources to ensure the accuracy of the weight assigned to each variable.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include wherein the at least one processor is configured to: compare sizes of the plurality of weight values, and determine the predetermined number of weight values among the plurality of weight values with larger sizes based on the result of the comparison as taught by Collins with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Sanexa in view of Singh in order to provide accurate information about the characteristics and demands of potential markets ([C1L19-24]).
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hewitt et al (US 2020/0111129) in view of Chopra et al (US 2021/0073267) in view of Saxena et al (US 11,245,966) in view of Singh (US 2016/0125473) in view of Acharya et al (US 2018/0232657)
Hewitt in view of Chopra in view of Saxena in view of Singh teaches the limitations of claim 11. As per claim 19:
Hewitt teaches:
wherein the plurality of weight values are: identified, based on the specific product being a first product, based on {…} first product attribute information of the first specific product, and identified, based on the specific product being a second product, {…} second product attribute information of the second specific product; and wherein the first product attribute information and the second product attribute information are at least partially different. ([0032] In one embodiment, the information handling system accurately identifies traits to the user's popularity and correlates the traits with the appropriate product, services, etc., to find the right business to alert for advertisement potential. In another embodiment, a user may possess a certain physical or other characteristic(s) that have made them popular (teeth, hair, fashion sense, athletic ability) which is prominent in their online profile. In this embodiment, the information handling system correlates the user's physical characteristics to related businesses, such as correlating a user with long hair to a shampoo company. [0035] Agent management engine 300 captures product data 330 from business 310 and from computer networks 200. Product data 330 informs agent management engine 300 about business 310's brand, which business 310 manually provides or agent management engine 300 extracts from computer networks 200. For example, business 310 may identify qualities or characteristics of users that should be measured, such as “Great Hair”, “Great Smile”, “Over 2000 Followers”, “Has Influence in the United States.” [0059] FIG. 6 is an exemplary high-level flowchart showing steps taken to select designated agents to promote a business' product or service. FIG. 6 processing commences at 600 whereupon, at step 610, the process captures branding characteristics (business characteristics) pertaining to the business' brand, such as their type of product/service, their overall business brand attributes (wholesome, edgy, reliable, etc.). At step 620, the process identifies preferred user traits corresponding to the branding characteristics (e.g., clean cut, long hair, tall, etc.).) Examiner’s comment: In in re Harza, 274 F.2d 669, 124 USPQ 378 (CCPA 1960), the courts held that mere duplication of parts has no patentable significance unless a new and unexpected result is produced. As the claim merely repeats the steps for a second product without presenting any new or unexpected result, the limitation has little to no patentable weight.)
Hewitt in view of Chopra in view of Saxena in view of Singh does not expressly teach wherein based on a reference matrix.
Acharya teaches:
identified… based on a reference matrix. (paragraph [0134] In various embodiments, data curation 810 operations are performed on a corpus, such as a product catalog, to generate a product-by-feature matrix ‘Y’ 806 and a product-by-user-interaction matrix ‘B’ 808. As used herein, a feature broadly refers to an attribute, and a user interaction broadly refers to any interaction a user may have with a given product. [0135] In these embodiments, each row of the product-by-feature matrix ‘Y’ 806 represents a particular product d and each column corresponds to a particular feature v associated with that product)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include identified… based on a reference matrix as taught by Acharya with the matching of products to potential endorsers of Hewiit in view of Chopra in view of Sanexa in view of Singh in order to provide actionable insights when it is combined with readily-available data ([0004]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER STROUD whose telephone number is (571)272-7930. The examiner can normally be reached Mon. - Fri. 9AM-5PM.
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, Waseem Ashraff can be reached at (571) 270-3948. 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.
CHRISTOPHER STROUD
Primary Examiner
Art Unit 3621
/CHRISTOPHER STROUD/Primary Examiner, Art Unit 3621
Prosecution Insights