DETAILED ACTION
Status of the Claims
This office action is submitted in response to the application filed on 1/27/25.
Examiner notes that this application claims priority from provisional applications 63625462 and 63671962.
Examiner further notes Applicant’s priority date of 1/26/24, which stems from the aforementioned provisional applications.
Claims 1-19 are currently pending and have been examined.
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 .
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Independent claims 1, 11, 14, and 19, in part, describe an invention comprising: (1) establishing a framework of psychological archetypes associated with emotions, (2) analyzing brand-related visual images to identify and score emotions they convey, (3) performing mathematical calculations (summing, multiplying, weighting) on the emotion scores, and (4) mapping the calculated scores to psychological archetypes or personality assessment models to evaluate brand personality. Claim 19 further recites translating personality traits from one assessment model to categorical key qualities of a Brand Palette Framework and cross-mapping those qualities to visual manifestations/mood boards. As such, the invention is directed to the abstract idea of brand personality assessment through psychological evaluation and mathematical analysis, which, pursuant to MPEP 2106.04(a), is aptly categorized as a mental process and a method of organizing human activity (specifically, marketing and advertising activities). Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
Next, the aforementioned claims recite additional elements including: graphical displays and visual representations for presenting the results of the mental processes and mathematical calculations. These limitations are recited at a high level of generality, and appear to be nothing more than field-of-use limitations (applying the abstract idea to brand imagery) and insignificant post-solution activity (displaying the results), with claims 11-13 adding generic computer components to automate the mental processes. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 134 S. Ct. at 2358, 110 USPQ2d at 1983. See also 134 S. Ct. at 2389, 110 USPQ2d at 1984.
Furthermore, looking at the elements individually and in combination, under Step 2A, Prong Two, the claims as a whole do not integrate the judicial exception into a practical application because they fail to: improve the functioning of a computer or a technical field, apply the judicial exception in the treatment or prophylaxis of a disease, apply the judicial exception with a particular machine, effect a transformation or reduction of a particular article to a different state or thing, or apply the judicial exception beyond generally linking the use of the judicial exception to a particular technological environment. Rather, the claims merely use mental processes and mathematical calculations to perform brand personality assessment, with claims 11-13 merely using a computer as a tool to perform the abstract idea(s), and/or add insignificant extra-solution activity to the judicial exception (e.g., graphical displays), and/or generally link the use of the judicial exception to a particular technological environment (e.g., a generic computer).
Next, under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Simply put, as noted above, there is no indication that the combination of elements improves the functioning of a computer (or any other technology), and their collective functions merely add field-of-use limitations and insignificant post-solution activity to the underlying mental processes and mathematical calculations.
Additionally, pursuant to the requirement under Berkheimer, the following citations are provided to demonstrate that the additional elements, identified as extra-solution activity, amount to activities that are well-understood, routine, and conventional. See MPEP 2106.05(d).
Outputting/Presenting data to a user. Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); MPEP 2106.05(g)(3).
Thus, taken alone and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea), and are ineligible under 35 USC 101.
Claims 2-10, 12-13, and 15-18 are dependent on the aforementioned independent claims, and further limit the abstract idea with details as follows:
graphically illustrating intensity values on the archetypal palette (claim 2);
establishing a quantitative scoring framework (claim 3);
establishing an archetypal palette of characters configured to identify and map embodied emotions (claim 4);
specifying particular types of brand-related visual images: brochures, catalogs, websites, social media posts (claim 5);
analyzing images and assigning intensity scores based on emotion strength (claim 6);
multiplying intensity scores by a multiplier (claim 7);
color-mapping intensity values onto the archetypal palette (claim 8);
compiling translation cross-maps between embodied emotions and different personality assessment models (claim 9);
cross-mapping emotion scores to different personality assessment models (claim 10);
weighting assigned discrete intensity values (claim 12);
categorizing calculated total scores (claim 13);
personality scores comprising intensity values for embodied emotions (claim 15);
assigning weighting factors to intensity values in translation cross-maps (claim 16);
scoring brand-related visual images (claim 17); and
summing embodied emotion scores to yield total values (claim 18).
These claims merely specify particular implementation details, additional mathematical operations (multiplying, weighting, categorizing), particular output formats (graphical illustrations, color-mapping), particular field-of-use limitations (types of visual images), or particular data manipulation activities (translation cross-maps). They do not affect an improvement in the functioning of the computer itself, in image analysis technology, or in any other technical field.
The recitation of "graphically illustrating" (claim 2), "color-mapping" (claim 8), and similar visual presentation elements are conventional methods of data display and constitute insignificant post-solution activity. They do not integrate the abstract idea into a practical application or provide a technological improvement. See MPEP 2106.05(f).
The recitation of "translation cross-map" and "cross-mapping" (claims 9-10, 16) merely adds another layer of mental process (mapping between different personality frameworks) and mathematical relationships. These are abstract concepts of data correlation and conversion that can be performed mentally or with pen and paper, and do not provide significantly more than the underlying abstract idea.
The specification of particular types of brand-related visual images (claim 5) is a descriptive field-of-use limitation that does not integrate the abstract idea into a practical application. Bilski v. Kappos, 561 U.S. at 612.
Therefore, claims 1-19 are not drawn to eligible subject matter, as they are directed to an abstract idea without significantly more.
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.
Claims 1-6 and 11 are rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju et al. (US 2017/0061448 A1) in view of Peng et al. (US 2015/0213331 A1).
Claim 1: Akkiraju discloses a method for mapping brand imagery comprising the steps of:
"establishing an archetypal palette comprising a matrix array of a plurality of psychological archetypes each associated with a plurality of embodied emotions" (Abstract; Paragraphs 0028 and 0030-(0031; Fig. 3. Akkiraju discloses a brand personality assessment system that establishes a structured brand personality framework. At Paragraph (0028), Akkiraju discloses that "The most known brand personality measure was developed in 1997 by J. L. Aaker" and at Paragraph (0030) discloses establishing a brand personality framework using the Aaker brand personality scale comprising "42 traits grouped into five large dimensions: sincerity, excitement, competence, sophistication, and ruggedness." Each dimension (psychological archetype) is associated with multiple personality traits and characteristics. For example, the sincerity dimension includes traits like down-to-earth, honest, wholesome, and cheerful; the excitement dimension includes daring, spirited, imaginative, and up-to-date traits at Paragraph (0030). This discloses establishing an archetypal palette of psychological archetypes, each associated with multiple characteristics/emotions.); and
"summing all the embodied emotion scores for said visual advertisement to yield a total value for each of said plurality of psychological archetypes" (Abstract; Paragraphs 0033-0035; Fig. 3. The system calculates personality gaps by analyzing brand personality dimensions. At Paragraph (0034), the system computes gaps for each of the five personality dimensions by comparing inferred and intended personalities, which inherently requires summing or aggregating individual trait scores to yield total values for each psychological archetype dimension.).
Akkiraju discloses the trait scores described above, but does not explicitly describe "scoring each of said embodied emotions in a brand-related visual image by analyzing said image, scoring each of said embodied emotions in said visual image, and assigning a quantitative intensity value thereto."
Peng, however, discloses "scoring each of said embodied emotions in a brand-related visual image by analyzing said image, scoring each of said embodied emotions in said visual image, and assigning a quantitative intensity value thereto" (Abstract; Paragraphs (0029)-(0031); Fig. 2. Peng discloses analyzing visual images to generate quantitative emotion metrics. At Paragraph (0029), "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200, where each dimension represents some basic emotion." At Paragraph (0030), "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized" and "an emotion vector represents a point in emotion space 200." The system analyzes image features and assigns quantitative intensity values (normalized vector elements) for each emotion dimension.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Peng with those of Akkiraju. One would have been motivated to do this in order to provide automated, quantitative analysis of brand-related visual images (such as advertisements, websites, and social media posts) to determine their psychological archetype scores, rather than relying solely on subjective human assessment or survey-based approaches as in Akkiraju. The combination would enable objective scoring of emotions conveyed by brand imagery and mapping those emotion scores to psychological archetype dimensions, thereby providing a comprehensive automated brand personality assessment system.
Claim 2: Peng further discloses "a step of graphically illustrating the intensity values assigned to all of said embodied emotions on said archetypal palette" (Paragraphs 0029-0030, 0039; Fig. 2. Peng discloses at Paragraph 0029 that "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200, where each dimension represents some basic emotion." At Paragraph 0030, "an emotion vector represents a point in emotion space 200" and "emotions in the dimensions of emotion space 200 can be arranged in a vector." Figure 2 shows the emotion space 200 graphically illustrating the emotion dimensions and intensity values as points plotted in the three-dimensional emotion space, thereby graphically illustrating intensity values assigned to emotions on a dimensional framework.).
The rationale for combining Peng with Akkiraju is articulated above and reincorporated herein.
Claim 3: Peng further discloses "a step of establishing a quantitative scoring framework" (Paragraphs 0029-0030; Fig. 2. Peng discloses at Paragraph 0029 that "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200, where each dimension represents some basic emotion." At Paragraph 0030, "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized," establishing a quantitative scoring framework with defined emotion dimensions and normalized numerical values for scoring.).
The rationale for combining Peng with Akkiraju is articulated above and reincorporated herein.
Claim 4: Akkiraju further discloses "wherein said step of establishing an archetypal palette comprises establishing an archetypal palette of characters configured to identify and map embodied emotions sought to be evoked" (Abstract; Paragraphs 0003, 0030-0031. Akkiraju discloses at Paragraph 0003 that "brand personality refers to a set of human characteristics associated with a brand" and brands seek to convey specific personalities to consumers. At Paragraph 0030, the system establishes a brand personality framework using "42 traits grouped into five large dimensions: sincerity, excitement, competence, sophistication, and ruggedness," where each dimension represents a character archetype with associated personality traits. These archetypal characters are configured to identify brand personalities and map the emotions that brands seek to evoke in their target audiences.).
Claim 5: Peng further discloses "wherein said brand-related visual image comprises any one from among the group consisting of a brochure, catalog, website, and social media post" (Abstract; Paragraphs 0025-0026. Peng discloses analyzing "an image" for emotion content at Paragraph 0025. At Paragraph 0026, the system receives and processes digital images to generate emotion metrics. Brochures, catalogs, websites, and social media posts all contain or comprise digital images that would be analyzed using Peng's emotion analysis system.).
The rationale for combining Peng with Akkiraju is articulated above and reincorporated herein.
Claim 6: Peng further discloses "wherein said step of scoring each of said embodied emotions comprises analyzing said brand-related visual image, assigning an intensity score for each of said embodied emotions based on the strength by which said brand-related visual image evokes said embodied emotion" (Abstract; Paragraphs 0029-0030; Fig. 2. Peng discloses at Paragraph 0029 that "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200, where each dimension represents some basic emotion." At Paragraph 0030, "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized" where "an emotion vector represents a point in emotion space 200." The system analyzes the visual image and assigns intensity scores for each emotion dimension, with the vector element values representing the strength of each emotion conveyed by the image.).
The rationale for combining Peng with Akkiraju is articulated above and reincorporated herein.
Claim 11: Akkiraju discloses a computer method for mapping brand imagery comprising the steps of:
"establishing an archetypal palette of characters configured to identify and map embodied emotions sought to be evoked" (Abstract; Paragraphs 0003, 0028, 0030-0031. Akkiraju discloses at Paragraph (0003) that "brand personality refers to a set of human characteristics associated with a brand" and brands seek to convey specific personalities to consumers. At Paragraph (0028), Akkiraju discloses that "The most known brand personality measure was developed in 1997 by J. L. Aaker" and at Paragraph (0030) discloses establishing a brand personality framework using "42 traits grouped into five large dimensions: sincerity, excitement, competence, sophistication, and ruggedness," where each dimension represents a character archetype with associated personality traits. These archetypal characters are configured to identify brand personalities and map the emotions that brands seek to evoke in their target audiences.);
"calculating total scores attributable to each embodied emotion for each character of said archetypal palette of characters" (Paragraphs 0033-0035. Akkiraju discloses at Paragraph (0034) that the system computes gaps for each of the five personality dimensions, which requires calculating total scores for each dimension/character by aggregating individual trait scores.); and
"mapping the total scores into a visual map that ranks characters within the archetypal palette of characters that are primarily motivated by the instance of visual promotional content" (Paragraphs 0033-0035, 0129-0130; Fig. 7B. Akkiraju discloses at Paragraphs (0033)-(0035) that the system computes values for each of the five personality dimensions (the character archetypes) by aggregating individual trait scores to yield total values for each dimension. At Paragraphs (0129)-(0130), Akkiraju discloses that the visualization groups the personality traits into the five dimensions (Sincerity, Excitement, Competence, Sophistication, and Ruggedness) and shows brands clustered on each dimension with medians of their values, thereby mapping the total scores for each character archetype into a visual representation that shows which personality dimension characters are most strongly represented by the visual promotional content.).
Peng, however, discloses "assigning a range of discrete intensity values to each embodied emotion of each character of the archetypal palette of characters" (Paragraphs (0029)-(0030); Fig. 2. Peng discloses at Paragraph (0029) that "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200" and at Paragraph (0030) that "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized," thereby establishing a range of normalized discrete intensity values for each emotion dimension.); and
"scoring an instance of visual promotional content by assigning a discrete intensity value to each embodied emotion representing tendency of said visual promotional content to elicit each such embodied emotion" (Abstract; Paragraphs (0029)-(0030); Fig. 2. Peng discloses analyzing visual images and assigning intensity values for each emotion dimension, where "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized" at Paragraph (0030), providing discrete intensity values for each emotion.).
The rationale for combining Peng with Akkiraju is articulated above and reincorporated herein.
Claims 7 and 12 are rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju/Peng in view of Ahn et al. (US 2014/0095570 A1).
Claim 7: The Akkiraju/Peng combination discloses those limitations cited above, but does not appear to explicitly describe a method "wherein said step of scoring each of said embodied emotions further comprises multiplying each assigned intensity score for each of said embodied emotions by a multiplier."
Ahn, however, discloses "wherein said step of scoring each of said embodied emotions further comprises multiplying each assigned intensity score for each of said embodied emotions by a multiplier" (Abstract; Claim 1. Ahn discloses a method for calculating personality and emotion scores comprising "multiplying an input value obtained from a sensor with a first personality set in accordance with at least one low rank element contained in at least one high rank element of a NEO PI-R (Revised NEO Personality Inventory)" and "calculating a personality factor value in a Five-Factor Model of the personality by adding the results of the multiplication," thereby explicitly teaching multiplying emotion/personality scores by a multiplier to calculate weighted values.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Ahn with those of Akkiraju/Peng. One would have been motivated to do this in order to provide weighted emotion scoring that accounts for the relative importance or significance of different emotions within each psychological archetype, allowing certain emotions to contribute more heavily to the overall archetype score based on their relevance to that particular archetype's characteristics.
Claim 12: Ahn further discloses "wherein said calculating step further comprises weighting each assigned discrete intensity value" (Abstract; Claim 1. Ahn discloses "multiplying an input value obtained from a sensor with a first personality set" and "calculating a personality factor value in a Five-Factor Model of the personality by adding the results of the multiplication," thereby weighting intensity values through multiplication before calculating total scores.).
The rationale for combining Ahn with Akkiraju/Peng is articulated above and reincorporated herein.
Claim 8 is rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju/Peng/Ahn in view of Burns (US 2016/0283093 A1).
The Akkiraju/Peng/Ahn combination discloses those limitations cited above, but does not appear to explicitly describe a method "wherein said step of graphically illustrating the multiplied intensity values assigned to all of said embodied emotions comprises color-mapping onto said archetypal palette."
Burns, however, discloses "wherein said step of graphically illustrating the multiplied intensity values assigned to all of said embodied emotions comprises color-mapping onto said archetypal palette" (Abstract; Paragraphs 0024-0025, 0042; Figs. 1-2. Burns discloses at Paragraph 0024 that "the sentiment includes an intensity level and an emotion level" where "the intensity level is one of multiple intensity levels that change along a first dimension of the color spectrum, and the emotion level is one of multiple emotion levels that change along a second dimension of the color spectrum." At Paragraph 0042, "different colors...representing different emotion levels" and "variations in intensity of color...representing different intensity levels," thereby color-mapping emotion intensity values onto a visual display.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Burns with those of Akkiraju/Peng/Ahn. One would have been motivated to do this in order to provide an intuitive, visually appealing representation of the weighted emotion scores using color gradients and mapping, allowing users to quickly perceive patterns and relationships between emotions and archetypes through color associations rather than numerical displays alone.
Claims 9-10, 14-15, 17-18 are rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju/Peng in view of Swayambhu et al. (US 9,667,367 B2).
Claim 9: The Akkiraju/Peng combination discloses those limitations cited above, but does not explicitly describe a method including "a step of compiling a translation cross-map of each of said embodied emotion scores to a different personality assessment model."
Swayambhu, however, further discloses "a step of compiling a translation cross-map of each of said embodied emotion scores to a different personality assessment model" (Abstract; Col. 9, lines 39-63; Fig. 7B, block 740. Swayambhu discloses a content personality classifier that correlates emotion/preference scores with personality assessment frameworks. The Abstract discloses "receiving ratings of a chosen contents from the customer; identifying the customer's Myers-Briggs Type Indicator based on the received ratings," thereby cross-mapping ratings/emotion scores to a personality assessment model (MBTI). At Col. 9, lines 49-54, "if a thumbnail or poster receives a rating of five, then the MBTI (e.g., ISFJ) or personality characteristic(s) (e.g., I, IS, etc.) belonging to the thumbnail or poster is/are assigned this rating factor. In this way, each personality characteristic(s) or MBTI may accumulate a rating score," thereby compiling a cross-map between emotion/preference scores (ratings) and a personality assessment model (MBTI).).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Swayambhu et al. with those of Akkiraju/Peng. One would have been motivated to do this in order to enable interoperability between the brand emotion archetype system and other established personality assessment frameworks such as Myers-Briggs, Big Five, or DISC, thereby allowing brand personality insights to be translated into formats compatible with existing personality assessment tools used by marketers and psychologists.
Claim 10: Swayambhu further discloses "a step of cross-mapping every embodied emotion score to said different personality assessment model using said translation cross-map" (Col. 9, lines 49-54, 61-63; Fig. 7B, block 740. Swayambhu discloses at Col. 9, lines 49-54, that rating scores accumulate to personality characteristics/MBTI, and at Col. 9, lines 61-63, "content personality classifier 110 may calculate the MBTI of the customer" based on the accumulated rating scores, thereby cross-mapping emotion scores to the personality assessment model using the compiled correlation framework.).
The rationale for combining Swayambhu with Akkiraju/Peng is articulated above and reincorporated herein.
Claim 14: Akkiraju further discloses a method for translating personality traits to an archetypal palette comprising:
"establishing an archetypal palette comprising a matrix array of a plurality of psychological archetypes each associated with a plurality of embodied emotions" (Abstract; Paragraphs 0030-0031; Fig. 3. Akkiraju discloses establishing a brand personality framework using "42 traits grouped into five large dimensions: sincerity, excitement, competence, sophistication, and ruggedness" at Paragraph 0030, where each dimension (psychological archetype) is associated with multiple personality traits and emotions.); and
"summing all the embodied emotion scores for said visual advertisement to yield a total value for each of said plurality of psychological archetypes" (Paragraphs 0033-0035; Fig. 3. At Paragraph 0034, the system computes gaps for each of the five personality dimensions by comparing personality scores, which requires summing individual trait scores to yield total values for each archetype dimension.).
Akkiraju, however, does not explicitly describe "scoring each of said embodied emotions in a brand-related visual image by analyzing said image, scoring each of said embodied emotions in said visual image, and assigning a quantitative intensity value thereto."
Peng, however, discloses "scoring each of said embodied emotions in a brand-related visual image by analyzing said image, scoring each of said embodied emotions in said visual image, and assigning a quantitative intensity value thereto" (Abstract; Paragraphs 0029-0030; Fig. 2. Peng discloses at Paragraph 0029 that "three dimensions di (iε{1, 2, 3}) are defined in an emotion space 200, where each dimension represents some basic emotion." At Paragraph 0030, "emotions in the dimensions of emotion space 200 can be arranged in a vector, and normalized" where the system analyzes visual images and assigns quantitative intensity values for each emotion dimension.).
Akkiraju and Peng, however, do not explicitly describe "compiling a translation cross-map of a plurality of personality traits within said first personality assessment model to each of said plurality of embodied emotions within said archetypal palette of characters" or "cross-mapping every weighted personality trait from said first personality assessment model to said archetypal palette of characters using said translation cross-map."
Swayambhu, however, discloses "compiling a translation cross-map of a plurality of personality traits within said first personality assessment model to each of said plurality of embodied emotions within said archetypal palette of characters" and "cross-mapping every weighted personality trait from said first personality assessment model to said archetypal palette of characters using said translation cross-map" (Abstract; Col. 9, lines 39-63; Fig. 7B, block 740. Swayambhu discloses at the Abstract "receiving ratings of a chosen contents from the customer; identifying the customer's Myers-Briggs Type Indicator based on the received ratings." At Col. 9, lines 49-54, personality characteristics accumulate rating scores (weighted values), and at Col. 9, lines 61-63, the system uses these weighted scores to determine personality types, thereby compiling translation cross-maps and cross-mapping weighted personality traits to personality assessment frameworks.).
The rationale for combining Akkiraju, Peng, and Swayambhu is articulated above and reincorporated herein.
Claim 15: Swayambhu further discloses "wherein said personality scores from said first personality assessment model comprise an intensity value for each of a plurality of embodied emotions" (Abstract; Col. 9, lines 39-63. Swayambhu discloses at the Abstract "receiving ratings of a chosen contents from the customer" where ratings represent intensity values. At Col. 9, lines 49-54, personality characteristics accumulate rating scores where "each personality characteristic(s) or MBTI may accumulate a rating score," thereby providing intensity values for personality characteristics.).
The rationale for combining Akkiraju, Peng, and Swayambhu is articulated above and reincorporated herein.
Claim 17: Peng further discloses "a step of scoring a brand-related visual image by analyzing said image, scoring each of said embodied emotions in said visual image, and assigning a quantitative intensity value thereto" (Abstract; Paragraphs 0029-0030; Fig. 2. Peng discloses analyzing visual images and assigning quantitative intensity values for each emotion dimension as normalized vector elements.).
The rationale for combining Akkiraju, Peng, and Swayambhu is articulated above and reincorporated herein.
Claim 18: Akkiraju further discloses "a step of summing all the embodied emotion scores for said visual image to yield a total value for each character in said plurality of archetypal palette of characters" (Paragraphs 0033-0035. Akkiraju discloses at Paragraph 0034 that the system computes gaps for each of the five personality dimensions, which requires summing individual trait scores to yield total values for each archetype dimension.).
Claim 13 is rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju/Peng/Ahn in view of Jung et al. (US 2011/0004577 A1).
The Akkiraju/Peng/Ahn combination discloses those limitations cited above, but does not appear to explicitly describe a method "wherein said calculating step further comprises categorizing each calculated total scores attributable to each embodied emotion for each character of said archetypal palette of characters."
Jung, however, discloses "wherein said calculating step further comprises categorizing each calculated total scores attributable to each embodied emotion for each character of said archetypal palette of characters" (Abstract; Claim 4. Jung discloses at Claim 4 that "the user's response is classified as a positive response or a negative response of a particular intensity" and "the personality updating unit is further configured to classify the user's response as the positive response or the negative response with reference to a response classification tree," thereby teaching categorizing emotion and personality scores into classifications based on their calculated values.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Jung with those of Akkiraju/Peng/Ahn. One would have been motivated to do this in order to organize and present the calculated emotion scores in meaningful categories (such as high/medium/low intensity levels or positive/negative emotions) that facilitate easier interpretation and comparison of brand personality characteristics across different archetypes.
Claim 16 is rejected under 35 U.S.C. § 103 as being unpatentable over Akkiraju/Peng/Swayambhu in view of Ahn (US 2014/0095570 A1).
The Akkiraju/Peng/ Swayambhu combination discloses those limitations cited above, but does not appear to explicitly describe a method "wherein said step of compiling a translation cross-map comprises assigning a weighting factor to every intensity value for each of a plurality of embodied emotions."
Ahn, however, discloses "wherein said step of compiling a translation cross-map comprises assigning a weighting factor to every intensity value for each of a plurality of embodied emotions" (Abstract; Claim 1. Ahn discloses "multiplying an input value obtained from a sensor with a first personality set in accordance with at least one low rank element contained in at least one high rank element of a NEO PI-R (Revised NEO Personality Inventory)" and calculating personality factor values, thereby assigning weighting factors (multipliers) to intensity values when translating between personality frameworks.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine this feature of Ahn with those of Akkiraju/Peng/Swayambhu. One would have been motivated to do this in order to provide weighted translation cross-maps that account for the varying importance of different personality traits when converting between different personality assessment models, ensuring that more relevant traits have greater influence in the translation.
Claim 19 is rejected under 35 U.S.C. § 103 as being unpatentable over Choi et al. (US 2021/0186398 A1) in view of Emanuel et al. (US 9,251,245 B2).
Choi discloses a method comprising "representing, by the device, the set of brand palette archetypes with a plurality of discrete visual manifestations" (Abstract; Paragraphs 0030, 0032-0033, and 0035; Table 1; Figs. 1 and 3; claim 1. Specifically, Choi discloses a personality testing system that represents personality types using discrete animal symbol images as visual manifestations of the determined personality characteristics. See, Choi, Abstract ("outputting images of a plurality of preset animals on a screen...determining a user personality type"); Paragraph 0030 ("each animal may have different characteristics...the different characteristics of the animals may be used to grasp the personality of the test subject"); Paragraph 0035, Table 1 (showing 30 animals corresponding to 10 different personality types/characteristics such as Goal/Achievement, Ideal/Escape, Initiative/Control, etc.); Figs. 1 and 3 (displaying discrete animal images on screen)).
Choi does not appear to explicitly describe a method for "mapping, by the device, the categorical key qualities to the set of brand palette archetypes using a translation cross-map."
Emanuel, however, discloses "mapping, by the device, the categorical key qualities to the set of brand palette archetypes using a translation cross-map" (Abstract; claim 1; col. 3, lines 55-65; col. 4, lines 20-35; Fig. 3. Emanuel discloses generating mappings between a plurality of taxonomies, wherein categories from a first taxonomy are mapped to categories of a second taxonomy (the "master taxonomy"), thereby creating a translation cross-map between different classification systems. See, Emanuel, Abstract ("mappings between taxonomies...from a category of a taxonomy to one or more categories within a master taxonomy"); col. 3, lines 55-65 (mapping sub-taxonomy categories to master taxonomy categories); col. 4, lines 20-35 (analyzing documents to determine mapping between taxonomy category and corresponding category of master taxonomy).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the filing date of the invention to combine these features of Emanuel with those of Choi. One would have been motivated to do this in order to create a more flexible and comprehensive personality assessment system that can translate between different classification frameworks (using Emanuel's cross-mapping technique) before representing the resulting categories with discrete visual symbols (per Choi's teaching), thereby enabling users to understand their personality or brand characteristics across multiple assessment models while maintaining intuitive visual communication.
Other Relevant Prior Art
Though not cited in the above rejections, the following references are nevertheless deemed to be relevant to Applicant’s disclosures:
De Oliveira et al. (20120284080), directed to a customer cognitive style prediction model based on mobile behavioral profile.
Bhan et al. (12333560), directed to a method and system of sentiment-based selective user engagement.
Mizokawa et al. (DE 69921563), directed to a system and method for controlling objects by simulating emotions and personality in the object.
Mascarenhas et al. (8010400), directed to a system and method for using psychological significance pattern information for matching with target information.
Forbes et al. (20120071785), directed to a system and method for assessing psychological characteristics.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER BUSCH whose telephone number is (571)270-7953. The examiner can normally be reached M-F 10-7.
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 Ashraf 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 C BUSCH/Examiner, Art Unit 3621
/WASEEM ASHRAF/Supervisory Patent Examiner, Art Unit 3621