DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4 December 2025 has been entered.
Status
This Office Action is in response to the communication filed on 11 May 2026. Claims 2-3, 5-6, 14-15, 22, and 27-29 have been cancelled currently or previously, no claims have been amended, and no new claims have been added. Therefore, claims 1, 4, 7-13, 16-21, 23-26, and 30 are pending and presented for examination.
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 .
Response to Amendment
A summary of the Examiner’s Response to Applicant’s amendment:
Applicant’s amendment overcomes the rejection(s) under 35 USC § 112; therefore, the Examiner withdraws the rejection(s).
Applicant’s amendment does not overcome the rejection(s) under 35 USC § 101; therefore, the Examiner maintains the rejection(s) while updating phrasing in keeping with current examination guidelines.
Applicant’s amendment does not overcome the prior art rejection(s) under 35 USC §§ 102 or 103; therefore, the Examiner maintains the rejection(s) as below.
Applicant’s arguments are found to be not persuasive; please see the Response to Arguments below.
Claim Interpretation
The Examiner notes that independent claims 1, 19, and 20 recite “receiving data indicative of a plurality of consumer categories, wherein each consumer category of the plurality of consumer categories comprises an indication of at least one of a demographic category, an interest, or a lifestyle characteristic of a type of consumer represented by the respective consumer category” (quoting claim 1, claims 19 and 20 being the same or parallel phrasing). Where this had been rejected as indefinite, further consideration indicates that this is apparently indicating the receiving of ANY data that can or could be classified in some manner. There is no indication of any preset or predetermined categories such that the data received would have to fit within any of those categories, so “data indicative of … categories”, including a demographic, interest or lifestyle of a consumer would appear to include any data the Examiner has been able to imagine or consider reasonable as received. For instance, the data collected from the panel of users would appear (since being indicative of content consumed) to be able to be categorized however someone may want, including at least by demographics and/or interest (i.e., consumption indicating interest). This is to say that since there is no indication of predetermined categories, the claim apparently includes any data that can be classified – that data indicates the categories, and it appears that the recited types of categories would generally encompass the data that can be received.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 4, 7-13, 16-21, 23-26, and 30 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claims 1, 19, and 20 each recite “wherein the panel of users and the first audience of users do not share any users in common”. The Examiner has searched for this concept and does not find it. Audience targeting is discussed (e.g., generally, Applicant ¶¶ 9-10, as submitted, 0011-0012 as published), and panel information such as a panel-centric database and panel data (e.g., generally, Applicant ¶¶ 14-25, as submitted, 0016-0027 as published), and that a target audience may be selected (e.g., Applicant ¶¶ 61 and 67, as submitted, 0063 and 0069 as published, indicating, e.g., game console users as the target audience); however, there does not appear to be any indication of the negative limitation that the first audience (i.e., the targeted audience) does not share any users in common with the panel of users – i.e., e.g., that a panelist would be blocked, prevented, etc. from being included in a targeted audience.
Claims 4, 7-13, 16-18, 21, 23-26, and 30 depend from claim 1, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 4, 7-13, 16-18, 21, 23-26, and 30 also lack written description support.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4, 7-13, 16-21, 23-26, and 30 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:
For analysis under SME Step 1, the claims herein are directed to a method (claims 1, 4, 7-13, 16-18, 21, 23-26, and 30), system (claim 19), and non-transitory computer-readable medium (claim 20), which would be classified under one of the listed statutory classifications (SME Step 1=Yes).
For analysis under revised SME Step 2A, Prong 1, independent claim 1 recites collecting, using a monitoring application installed on each device associated with users of a panel of users, data indicative of content consumed by the panel of users; determining a plurality of content categories associated with the content consumed by the panel of users, wherein each content category of the plurality of content categories comprises an indication of at least one of a theme, a subject matter, or a topic associated with the respective content category; receiving data indicative of a plurality of consumer categories, wherein each consumer category of the plurality of consumer categories comprises an indication of at least one of a demographic category, an interest, or a lifestyle characteristic of a type of consumer represented by the respective consumer category; receiving a contextual profile associated with a content category of the plurality of content categories; determining a correlation value between each of the plurality of consumer categories and the content category; averaging the correlation values of the plurality of consumer categories and the content category; determining that a correlation value of a consumer category of the plurality of consumer categories and the content category satisfies a threshold based on the average correlation; including, based on the correlation value satisfying the threshold, the consumer category in the contextual profile; and determining to insert supplemental content into second content provided to a first audience of users over a second period of time wherein the determination of what supplemental content to insert is based, at least in part, on one or more content categories of the plurality of content categories that are associated with the second content, wherein the panel of users and the first audience of users do not share any users in common wherein neither audience demographic information nor audience behavior information derived directly from the first audience of users is available, and wherein subject matter of the supplemental content is determined, based at least in part, on consumer categories included in contextual profiles associated with the one or more content categories of the plurality of content categories that are associated with the second content.
Independent claims 19 and 20 are parallel to claim 1 above, requiring the same activities, except being directed to a system comprising: at least one processor; and at least one memory storing instructions that, when executed, cause the at least one processor to perform the activities (at claim 19) and a non-transitory computer-readable medium storing instructions that, when executed, cause the activities to be performed (at claim 20).
The dependent claims (claims 4, 7-13, 16-18, 21, 23-26, and 30) appear to be encompassed by the abstract idea of the independent claims since they merely indicate to satisfy the threshold is based on comparing the consumer-content correlation to the threshold (claim 4), determining a correlation between a different consumer category does not satisfy the threshold and therefore determining that the different consumer category should not be associated with the profile associated with the content category (claim 7) where the threshold for determining the correlation with the different category is based on being less than or equal to the threshold (claim 8), determining the correlation with the different consumer category (at claim 7) satisfies the threshold and associating the different consumer category to the profile associated with the different content category (claim 9), at least one consumer category indicating a viewing habit category (claim 10), the data indicative of consumer categories comprises purchasing behavior (claim 11), web browsing behavior (claim 12), television watching habits (claim 13), HTTP requests (claim 21), where the device identifier is indicative of demographic information (claim 23), the consumed content being websites and the data indicative of that content being a URL, times the URL was consumed, or device ID (claim 16), the data indicative of consumer categories is accessed from a database (claim 17), using a regression model to determine correlation (claim 18), the monitoring application has access to the network stack of each device (claim 24), determining correlation comprises the correlation being greater than the threshold (claim 25), the supplemental content being obtained from a supplemental content provider (claim 26) and/or data indicative of content consumed comprises a language of the content (claim 30).
The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of “contextual targeting” per Applicant ¶ 2 – i.e., categorizing consumer segments and content to correlate them and associate a consumer category to a profile of a content category; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the certain methods of organizing human activity (e.g., … commercial or legal interactions such as … advertising, marketing or sales activities/behaviors, or business relations; …) grouping of subject matter, but also implicates mathematical concepts (e.g., … calculations) in the calculations of average correlations and satisfying a threshold.
The Examiner notes that How to Write Advertisements That Sell, specific author unknown, A.W. Shaw Co., 1912, advocates for classifying or categorizing both consumers and venues such as content types, summarizing the concepts in various charts to track the advertising (see, e.g., pp. 6, 40, 56, 64-65, etc.) where, for example, “The Advertising Chart has an important place here. By it a book publisher cleverly classifies his volumes in such a way that different groups of books, as advertised in the fiction monthly, the farm paper, the literary monthly, the news weekly, the morning paper, the religious weekly, the woman's journal and various class and trade publications respectively, make the widest possible appeal to those who are prospects for each.” (Id. at 28). The book is replete with other indications of categorizing consumers and content. This indicates that the content of various publications is categorized so that consumers that are categorized as correlating to that content category fit the associated profile for targeting.
Therefore, the claims are found to be directed to an abstract idea.
For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are using a monitoring application installed on each device (at claim 1), the claim to a system comprising: at least one processor; and at least one memory storing instructions that, when executed, cause the at least one processor to perform the activities (at claim 19), a non-transitory computer-readable medium storing instructions that, when executed, cause the activities to be performed (at claim 20), and the data being collected as including HTTP requests (at claim 21), URLs of web pages accessed, times the URL was accessed/consumed, and device identifier (at claim 16), and/or having access to a network stack of each device (at claim 24). These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
The indication of using an application installed on a panelist device is literally just a form of “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity
The collecting and forwarding of particular data (e.g., HTTP requests, URLs, times of access, device IDs, and/or content categories) as indicated at claims 1, 10-14, 16, 19-21, and 30 may be computer-related data, but there is no change or improvement to the collecting or gathering of data, nor the forwarding of the collected/gathered data. This is considered, based on MPEP § 2016.05(g) as insignificant extra-solution activity since “Mere Data Gathering” and/or “Selecting a particular data source or type of data to be manipulated”.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.
For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity.
No additional elements are identified as well-understood, routine, conventional (“WURC”) activity for consideration under the WURC rubric and/or Berkheimer.
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore, the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.
Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.
Allowable Subject Matter
Claims 1, 4, 7-13, 16-21, 23-26, and 30 are indicated as allowable over the prior art.
The following is a statement of reasons for the indication of allowable subject matter: Although the claims indicate contextual advertising and the closest art of record (Mielechowicz et al. (U.S. Patent Application Publication No. 2018/0047048, hereinafter Mielechowicz) in view of Huang et al. (U.S. Patent Application Publication No. 2019/0155916, hereinafter Huang) and in further view of Attenberg et al. (U.S. Patent Application Publication No. 2012/0010927, hereinafter Attenberg)) appears to address the claim elements as rejected at the previous rejections, the claims now also recite “wherein the panel of users and the first audience of users do not share any users in common, wherein neither audience demographic information nor audience behavior information derived directly from the first audience of users is available”. The Examiner does not find art that would exclude or prevent a panelist from being targeted or being part of a targeted audience. Further, it does not appear to make reasonable sense to include panelist information for analysis regarding content and consumer categories, but to also then prevent the panelist from being targeted – the panelist was, or likely was, targeted in some manner with the content they consumed, but that same targeting must then apparently be somehow turned off lest they be included in a/the target (i.e., first) audience.
Therefore, it does not appear reasonable to combine references so as to arrive at the currently claimed invention.
Response to Arguments
Applicant's arguments filed 11 May 2026 have been fully considered but they are not persuasive.
Applicant first argues the 112 rejections (Remarks at 9-11); however, since the rejections are withdrawn, the argument(s) is/are considered moot and not persuasive.
Applicant then argues the 101 rejections (Remarks at 11-13), repeating the allegation that since the claims use the content categories, the audience is predicted (since specific audience information is unavailable) and therefore “an improvement to prior art data collecting/gathering techniques, solving the technical problem of determining contextually-relevant content to serve to a particular audience of users, when the entity serving the content only knows the caterogry(ies) [sic] of content that it is serving to the particular audience-but it does not know any relevant demographic/behavioral information about the particular audience of users it is serving said content to” (Remarks at 12). However, first, prior art analysis and whether there is an improvement to prior art is not used in eligibility analysis. Second, this reflects the abstract idea of contextual targeting, and is included with the abstract idea – using that data (context, such as categories of users that have or tend to view content or a page) does not take the claims outside the realm of abstract ideas. The claims are still specifically in the advertising, marketing, etc. areas that are included in the certain methods of organizing human activity grouping.
Applicant then argues that “Indeed, it is the very technical details recited in the claims that take it outside the realm of an abstract idea (e.g., organizing human activity grouping). For example, technical solution details, such as: [1] receiving a contextual profile …; [2] determining a correlation value …; [3] averaging the correlation values …; and [4] determining to insert supplemental content” (Id at 13). However, the indicated activities are NOT “technical solution details” – there is no apparent invention, change, modification, improvement, problem, or solution related to receiving information (e.g., a contextual profile). The claims merely say to receive the information, i.e., by any means regardless of any technology that may be used, and this encompasses not using any actual technology at all – the receiving of a contextual profile at the claims can encompass receiving that information via snail mail. However, the Examiner has considered that the claims also encompass the receiving as being via some form of technology, but there still is no problem indicated with the receiving nor any solution to such a problem. The same or similar analysis is applied to determining and averaging correlation values – that is relatively simple mathematics a person can do (even mentally, or by use of pen/pencil and paper, if needed or desired). The same or similar analysis is also applied to determining to insert or place supplemental content – it is the primary basis of the abstract idea grouping. The indicated activities – even when considered as a whole or ordered combination – are merely the performing of the abstract idea. The claims – including being considered as a whole – infer interest (or a similar basis for insertion of supplemental content) based on the content and consumer categories derived from other persons (e.g., the panelists) behavior or viewing tendencies. As such, the claims – when considered as individual elements at Step 2A, Prong 1 and Prong 2, and when considered as a whole (including Step 2B) really just indicate the abstract idea and do not indicate a practical application, or significantly more than the abstract idea.
Applicant next argues the § 103 rejections (Remarks at 13-17); however, since the prior art rejections are withdrawn, the argument(s) is/are considered moot and not persuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ho, Betty, Targeting 101: Contextual vs. Behavioral Targeting, Criteo.com, 1 November 2018, downloaded from https://www.criteo.com/blog/contextual-vs-behavioral-targeting/ on 21 January 2022, indicating contextual targeting as a common and long-established form of advertising.
Nettleton, David, Pearson Correlation, Commercial Data Mining, 2014, downloaded from https://www.sciencedirect.com/topics/computer-science/pearson-correlation on 22 January 2022, indicating that “The Pearson correlation method is the most common method to use for numerical variables; it assigns a value between − 1 and 1, where 0 is no correlation, 1 is total positive correlation, and − 1 is total negative correlation. This is interpreted as follows: a correlation value of 0.7 between two variables would indicate that a significant and positive relationship exists between the two. A positive correlation signifies that if variable A goes up, then B will also go up, whereas if the value of the correlation is negative, then if A increases, B decreases.” (at 1), which appears to be a/the average correlation claimed, or is related to it.
Sheppard et al. (U.S. Patent Application Publication No. 2020/0202370, hereinafter Sheppard) discusses collecting panelist user impression information via an app of a client device, including HTTP requests and responses, URLs, mobile equipment identifier, and associated demographic information (Sheppard at least at 0021, 0024-0026, 0029-0030, 0034, 0039-0041, 0044-0045, 0104).
Brown (U.S. Patent No. 10,123,063) indicates that “user access to web content may be monitored using a panel-based approach or a beacon-based approach. A panel-based approach generally entails installing a monitoring application on the user devices of a panel of users that have agreed, in advance with informed consent, to have their devices monitored. The monitoring application then collects information about the webpage or other resource accesses and sends that information to a collection server” (Brown at 4:36-64).
Kurland et al. (U.S. Patent No. 4,603,232, hereinafter Kurland) indicates that as far back as 1984, “Market survey data collection systems are well known in the art” (Kurland at 1:13-14), and discloses “a method for independently centrally electronically accumulating market survey data from different content rapidly disseminated market surveys from a plurality of panelist stations located at diverse locations” (Kurland at 1:6-10), i.e., gathering content data from panelist devices.
Burbank et al. (U.S. Patent No. 8,930,701, hereinafter Burbank) discusses “decoding information from a mobile device into a plurality of encrypted identifiers identifying at least one of the mobile device or a user of the mobile device, sending ones of the encrypted identifiers to corresponding database proprietors, receiving a plurality of user information corresponding to the ones of the encrypted identifiers from the corresponding database proprietors, and associating the plurality of user information with at least one of a search term collected at the mobile device or a media impression logged for media presented at the mobile device” (at Abstract).
Sullivan et al. (U.S. Patent Application Publication No. 2017/0127133, hereinafter Sullivan) discusses “Methods, apparatus, and articles of manufacture are disclosed to categorize audience members by age. An example method disclosed herein includes assigning a weight to each audience member record. In the example method, the weight is based on a quantity of audience members in a same age group as the audience member record. The example method includes, at the child nodes, calculating an effective quantity of audience member records based on the weights of the audience member record assigned to the corresponding child node. In the example method, when the effective quantity of audience member records satisfies a minimum leaf size, splitting the corresponding child node into additional ones of the child nodes based on a corresponding child node attribute-value pair. In the example method, when the effective quantity of audience member records does not satisfy the minimum leaf size, designating the corresponding child node as a terminal node.” (at Abstract).
Laurent et al., Measuring Consumer Involvement Profiles, Journal of Marketing Research, Vol, XXII (February 1985), pp. 41-53, downloaded from https://web.p.ebscohost.com/ehost/pdfviewer/pdfviewer?vid=0&sid=b5226b61-9d48-4dca-b157-d1f9aa637a74%40redis indicating at least that “There is more than one kind of consumer involvement. Depending on the antecedents of involvement (e.g., the product's pleasure value, the product's sign or symbolic value, risk importance, and probability of purchase error), consequences on consumer behavior differ. The authors therefore recommend measuring an involvement profile, rather than a single involvement level. These conclusions are based on an empirical analysis of 14 product categories.” (at 41).
Nakano et al, Customer segmentation with purchase channels and media touchpoints using single source panel data, Journal of Retailing and Consumer Services, Vol. 41, March 2018, pp. 142-152, downloaded from https://www.sciencedirect.com/science/article/pii/S096969891730471X on 2 August 2023, indicating that “This study examines how customers use multiple channels and media in modern retail environments. It segments customers by using Latent-Class Cluster Analysis, which focuses on the purchase channels of bricks-and-mortar and online stores, media touchpoints of PC, mobile, and social media, and psychographic and demographic characteristics. It extends the framework of prior research by analyzing 2595 Japanese single source panelists’ data in which purchase scan panel data on low-involvement, more frequently purchased categories, media contact log data, and survey data are tied to the same ID. The analyses reveal seven segments including the properties of research shoppers and multichannel enthusiasts.” (at 142, Abstract).
Leary et al. (U.S. Patent Application Publication No. 2012/0278064, hereinafter Leary) discusses “The determined sentiment value(s) 123 may be stored in association with the user text content 105 and represent what is determined to be sentiment for the subject. After analysis, the given user text content 105 may be associated with sentiment value 123 that correlates to (i) the users sentiment for a particular facet or category of the subject in the user content (e.g. business establishment), and/or (ii) the users sentiment in general, on average, or overall when all facets and categories are considered. The sentiment value(s) 123 that is determined for the particular item of user text content 105 may be based on the sentiment score 104 for salient terms 111 that are relevant to the subject and or the subject categories. For example, the sentiment score 104 for individual terms that are extracted from the text content may be averaged (or categorized and then averaged), in order to determine sentiment for the subject and/or a particular predefined domain-relevant category” (Leary at 0039).
IAB, Understanding Brand Safety & Brand Suitability in a Contemporary Media Landscape, dated December 2020, downloaded from https://www.iab.com/wp-content/uploads/2020/12/IAB_Brand_Safety_and_Suitability_Guide_2020-12.pdf on 7 March 2024, indicating that “issues of Brand Safety have begun to evolve beyond avoidance of malware, spam, and adult content, to include larger and more difficult-to-pin-down considerations of Brand Suitability” (at 6), the “IAB’s Programmatic+Data Center convened a working group of the leading ad verification and ad tech companies, as well as media agencies, to develop best practices based on what we learned during this unprecedented year” (Id.), that “Brand Safety and Brand Suitability are ever-evolving” (Id, at 7), and after identifying some “Relevant Groups” (Id. at 8) indicates that “TAG defines “Brand Safety” as the controls that companies in the digital advertising supply chain use to protect brands against negative impacts on consumer opinion associated with specific types of content and/or related loss of return on investment” (Id.), but nevertheless, under “Defining Brand Safety” (Id.)
Brand Safety solutions enable a brand to avoid content that is generally considered to be inappropriate for any advertising, and unfit for publisher monetization regardless of the advertisement or brand. This is where the 4A’s Brand Safety Floor categorization and IAB’s taxonomy classifications come into play.
For example, content that contains hate speech directed at a protected class would be inappropriate for any advertising. Likewise, content that promotes or glamorizes the consumption of illegal drugs would be inappropriate for any advertising.
(Id. at 8-9).
Array Basics, FSU, downloaded 4 November 2024 from https://www.cs.fsu.edu/~myers/c++/notes/arrays.html indicates that
An array is an indexed collection of data elements of the same type.
Indexed means that the array elements are numbered (starting at 0).
The restriction of the same type is an important one, because arrays are stored in consecutive memory cells. Every cell must be the same type (and therefore, the same size).
(at p. 1).
Everything you wanted to know about arrays, Microsoft PowerShell, dated 20 June 2024, downloaded 4 November 2024 from https://learn.microsoft.com/en-us/powershell/scripting/learn/deep-dives/everything-about-arrays?view=powershell-7.4, indicating (similar to the above) that “An array is a data structure that serves as a collection of multiple items. You can iterate over the array or access individual items using an index. The array is created as a sequential chunk of memory where each value is stored right next to the other.” (at p. 1) with further indexing information at p. 4 et seq.
Busbee et al., Arrays and Lists, Rebus Community, copyrighted 2018, downloaded 4 November 2024 from https://press.rebus.community/programmingfundamentals/chapter/arrays-and-lists/, indicating that “An array is a data structure consisting of a collection of elements (values or variables), each identified by at least one array index or key” (at p. 1).
Soroca et al. (U.S. Patent Application Publication No. 2010/0094878, hereinafter Soroca) describes that “In embodiments of the present invention improved capabilities are described for using a monetization platform server to associate sponsored content with contextual information relating to mobile content, and storing the sponsored content-contextual information association in a data facility for future use in optimizing the delivery of a sponsored content to a mobile communication facility based at least in part on a display datum associated with the mobile communication facility, wherein the display datum includes a contextual datum” (at Abstract), including content categorization (Soroca at 0826-0827, 0891), user (i.e., consumer) profiles and categorization of a consumer (Soroca at 1387-1388, 1399, 1401, 1465).
Merriam-Webster, “Related” definition, downloaded 5 February 2026 from https://www.merriam-webster.com/dictionary/related, indicating what “related to” would mean at the claims.
Merriam-Webster, “Correlation” definition, downloaded 5 February 2026 from https://www.merriam-webster.com/dictionary/correlation, indicating what “correlation” would mean at the claims.
Word Reference forum, Correlated and Related, downloaded 5 February 2026 from https://forum.wordreference.com/threads/correlated-and-related.3740959/, dated 12 September 2020, indicating what “correlation” and “related to” would mean at the claims.
Editage.com, Answer to the question: What is the difference between “related to”, “correlated to” and “associated with”?, dated 30 May 2022, downloaded 5 February 2026 from https://www.editage.com/insights/what-is-the-difference-between-related-to-correlated-to-and-associated-with, indicating what “correlation” and “related to” would mean at the claims.
Falcon (U.S. Patent Application Publication No. 2012/0110027) indicates “A computer implemented method is provided for generating audience information for a population. The method includes the steps of recording reference media consumption information for a plurality of reference panel elements, recording mass media consumption information for a plurality of mass panel elements and determining a correspondence between portions for reference panel of the reference and mass media consumption information obtained. Said correspondence is used to link at least one of the reference panel elements to at least one of the mass panel elements in order to define a session including media consumption information recorded for the linked reference and mass panel elements and to define audience information for the population therefrom” (at Abstract).
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/SCOTT D GARTLAND/
Primary Examiner, Art Unit 3685
Prosecution Insights