DETAILED ACTION
Notice relating to Pre-AIA or AIA Status
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 24 DECEMBER 2025 has been entered.
Response to Arguments
Applicant’s arguments with respect to the claims have been considered but are moot because the arguments do not apply to the new reference(s) and/or citations being used in the current rejection.
Examiner’s Note
It is noted to Applicant that Allowable subject matter has been indicated in related Applications 15/219,262, 15/985,634, 16/883,935, and 17/938,033. Applicant is suggested to try and incorporate similar Allowable content into the current Application’s claims to try and move prosecution forward to an Allowance. Applicant is also cautioned not to repeat allowable subject matter in a manner that could lead to a double patenting rejection. This is just a note and suggestion by the Examiner, any amendments made by Applicant will be searched thoroughly before a final indication on Allowability is made.
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.
Claims 1-2, 4-8, 10, 12-13, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Kirillov et al., US 2016/0165277 in view of HSU et al., US 2016/0125471 and further in view of Perez et al., US 2015/0046579 and Lessin et al., US 2014/0143048.
Regarding claim 1, Kirillov discloses a method, comprising:
obtaining a data set associated with viewing of digital content (obtained data from STB log; page 2, paragraph 24, and Fig. 1, Block 3, and wherein STB log indicates viewing event(s); page 3, paragraph 33) across a plurality of device types (with plurality of deice types; page 4, paragraph 40);
calculating an audience metric based on the data (based on the certain viewing estimate/scores, which are at least partially derived from the data set, system can combine the data in order to estimate metrics; page 2, paragraph 25, and page 3, paragraphs 35-36, and Fig. 1, Blocks 4 and 5, and including metrics such as viewership in relation to content; pages 1-2, paragraph 16, and page 5, paragraph 55); and
generating a digital audience segment, for use in a programmatic advertising system (creation of promotional campaigns for use with sponsored content segments; page 1, paragraph 13, and page 4, paragraphs 43-44, and for use in a programmatic advertising system; page 4, paragraph 43).
Kirillov does not explicitly disclose matching at least a portion of a data set to at least one consumer in a consumer graph to obtain person matched data, wherein the matching links data from at least two of a plurality of device types to the at least one consumer;
calculating a deduplicated metric based on the person match data by counting unique consumers across the plurality of device types; and
a targetable segment based on the deduplicated metric, the segment comprising a subset of consumers within the consumer graph identified based on a threshold value associated with the deduplicated metric for each consumer, the segment comprising a list of identifiers for the consumers within the consumer graph.
In a related art, HSU does disclose matching at least a portion of a data set to at least one consumer in a consumer graph to obtain person matched data (system can utilize current data, i.e. data set, and match with at least user profile; pages 5-6, paragraph 54, and wherein the user profile consists of a graph with nodes and edges; page 5, paragraph 47, and Fig. 3A1), wherein the matching links data from at least two of a plurality of device types to the at least one consumer (matching to associate/link across multiple devices for particular user(s); page 6, paragraph 70, and page 8, paragraphs 85-86, and with plurality of device types; page 1, paragraph 4, and page 2, paragraph 26, and page 3, paragraph 33, and page 5, paragraph 54);
the person matched data (matched data can be utilized and combined; page 5, paragraph 51, and pages 5-6, paragraph 54, and using the specific combined profile/graph information for performing other operations; page 6, paragraph 70); and
a targetable segment, the segment comprising a subset of consumers within the consumer graph, and the segment comprising a list of identifiers for the consumers within the consumer graph (generation, and targeted segments based on the particular data, and wherein can include users who meet the criteria, i.e. subset; page 8, paragraphs 83 and 85-86, and will include IDs for users based on the data; pages 8-9, paragraphs 85-88, and again using a graph with nodes and edges; page 5, paragraph 47, and Fig. 3A1).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov and HSU by allowing user data sets to be matched based on current and past user data, in order to provide an improved system and method for associating or matching users across multiple devices and providing real-time synchronized user categories for users that have been identified as a single user (HSU; page 3, paragraph 35).
Kirillov in view of HSU does not explicitly disclose calculating a deduplicated metric based on person data by counting unique consumers across a plurality of device types; and
a segment based on the deduplicated metric, and consumers identified based on a threshold value associated with the deduplicated metric for each consumer.
In a related art, Perez does disclose calculating a deduplicated metric based on person data by counting unique consumers across a plurality of device types (determining metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163, and calculated based on unique audience/member(s), i.e. count; page 20, paragraph 166, and page 24, paragraph 204, and page 21, paragraph 170-171, and with plurality of device types; page 6, paragraphs 62 and 65); and
a targetable segment based on the deduplicated metric (generating/creating; page 4, paragraph 37, and targeted advertising based on the data; page 6, paragraph 70, and page 7, paragraph 74, and with additionally determined opportunities to serve ads to a target user/audience; page 4, paragraph 39, and targeting markets with future, i.e. generated, advertisement opportunities; page 3, paragraph 40), and the deduplicated metric (determining metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163, and calculated based on unique audience/member(s), i.e. count; page 20, paragraph 166, and page 24, paragraph 204, and page 21, paragraph 170-171).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, and Perez by allowing user data sets to be analyzed and modified/reduced, in order to provide an improved system and method for monitoring media and, more particularly, to de-duplicate impression information (Perez; page 1, paragraph 2).
Kirillov in view of HSU and Perez does not explicitly disclose consumers identified based on a threshold value associated with a metric for each consumer.
In a related art, Lessin does disclose consumers identified based on a threshold value associated with a metric for each consumer (determining cluster of users in relation to each user(s) of the cluster meeting a threshold metric; page 10, paragraphs 71-73).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, Perez, and Lessin by allowing users to be identified based on particular metric thresholds, in order to provide an improved system and method for audience-based advertising pricing which provides efficient mechanisms for differentiating between different types of audiences (Lessin; page 1, paragraphs 1 and 4).
Regarding claim 2, Kirillov in view of HSU, Perez, and Lessin discloses obtaining an incremental reach of the digital content relative to a population corresponding to the consumer graph based on the deduplicated audience metric (Kirillov; system can use the calculations to also estimate metrics related to incremental reach in relation to a population; page 2, paragraphs 17 and 21, and page 5, paragraphs 55-56, and page 6, paragraph 67, and HSU; using a graph with nodes and edges; page 5, paragraph 47, and Fig. 3A1, and Perez; metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163).
Regarding claim 4, Kirillov in view of HSU, Perez, and Lessin discloses the deduplicated audience metric is determined by source, and the source comprises one or more of linear content, digital content, video on demand content, or streaming video content (Kirillov; metric(s) for the content, wherein the content can be from particular source, such as linear broadcast, on-demand, streaming video, etc.; page 4, paragraph 45, and page 5, paragraph 48, and Perez; metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163, and in relation to source(s); page 5, paragraphs 53-54).
Regarding claim 5, Kirillov in view of HSU, Perez, and Lessin discloses the deduplicated audience metric is further deduplicated relative to the source (Kirillov; system can use the calculations to also estimate metrics; page 2, paragraph 21, and page 5, paragraphs 55-56, and page 6, paragraph 67, and wherein in relation to a source, such as linear broadcast, on-demand, streaming video, etc.; page 4, paragraph 45, and page 5, paragraph 48, and Perez; metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163, and in relation to source(s); page 5, paragraphs 53-54).
Regarding claim 6, Kirillov in view of HSU, Perez, and Lessin discloses the data set is obtained from more than one source and consumer data in the consumer graph is obtained from more than one source (Kirillov; data set logs and panelist data obtained from metered logs from households, i.e. more than one source, and/or from certain panel sources; page 5, paragraphs 49 and 51, and from cable or satellite sources; page 2, paragraph 20, and HSU; data for the consumer profile/graph can be obtained from various users/devices, i.e. sources, and combined; Fig. 1A, and page 3, paragraph 33, and pages 5-6, paragraph 54, and Fig. 8A, and page 9, paragraph 90, and again wherein user profile consists of a graph with nodes and edges; page 5, paragraph 47, and Fig. 3A1).
Regarding claim 7, Kirillov in view of HSU, Perez, and Lessin discloses the data set is obtained from aggregated data and panel data (Kirillov; combining, i.e. aggregating, log data and panel data; page 6, paragraph 67, and including panel data; page 5, paragraphs 49-50).
Regarding claim 8, Kirillov in view of HSU, Perez, and Lessin discloses the data set includes one or more of a digital content airing schedule and historical digital content viewing metrics (Kirillov; data includes at least the viewing date, time, signature, and panelist identity, i.e. schedule when aired; page 2, paragraph 18, and/or date, time, and channel, i.e. again schedule when aired; page 2, paragraph 22, and metrics relating to viewing, such as number of times exposed, i.e. historical metrics; page 5, paragraph 55).
Regarding claim 10, Kirillov in view of HSU, Perez, and Lessin discloses the deduplicated audience metric is based on a combination of a first prediction, a second prediction, and a third prediction (Kirillov; can be based on combining calculations, including various predictions, such as viewing predictions, i.e. more than one, and scoring calculations, which include prediction operations as well, i.e. indicating combining multiple, with at least 3, types of predictions; page 2, paragraph 25, and page 3, paragraphs 34-35, and Perez; metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163).
Regarding claim 12, Kirillov in view of HSU, Perez, and Lessin discloses the second prediction is a probabilistic estimate for individual views of the digital content (Kirillov; estimation can include probability prediction of an individual viewing; page 3, paragraph 35, and pages 6-7, paragraph 72).
Regarding claim 13, Kirillov in view of HSU, Perez, and Lessin discloses the third prediction is a prediction of viewership based on one or more characteristics associated with the digital content (Kirillov; prediction can include calculations with predictors based on demographics as well as characteristics of media, such as channel, genre, etc.; page 3, paragraph 31).
Claim 18, which discloses a system, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 1. The following additional limitations are also disclosed:
one or more computing devices (Kirillov; with at least computer(s); page 7, paragraph 76) operable to communicate with one or more memory systems (Kirillov; with coupled memory; page 7, paragraph 76) and one or more providers (Kirillov; with at least provider(s); page 1, paragraphs 12 and 14, and pages 4-5, paragraph 46).
Claim 19, which discloses a system, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 2.
Claims 3 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kirillov et al., US 2016/0165277 in view of HSU et al., US 2016/0125471, Perez et al., US 2015/0046579, and Lessin et al., US 2014/0143048, and further in view of Pecjak et al., US 8,874,652.
Regarding claim 3, Kirillov in view of HSU, Perez, and Lessin discloses all the claimed limitations of claim 1, as well as determining a first reach of the digital content relative to a first source (Kirillov; can determine first reach in relation to television source(s); page 6, paragraph 68);
determining a second reach of the digital content relative to a second source (Kirillov; can determine at least second reach in relation to online source(s); page 6, paragraph 68); and
determining based on the reach (Kirillov; can make further determinations/calculations based on the determined reach calculation(s); page 6, paragraph 68).
Kirillov in view of HSU, Perez, and Lessin does not explicitly disclose determining a reach overlap of a first reach and a second reach.
In a related art, Pecjak does disclose determining a reach overlap of a first reach and a second reach (based on expected and incremental reach determinations, system can then determine a reach overlap adjustment, i.e. for determined overlap; col. 17, line 20 – col. 18, line 31).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, Perez, Lessin, and Pecjak by allowing determination of overlap for the already calculated reach metrics in Kirillov in view of HSU, Perez, and Lessin, in order to provide and improved system and method for accounting for overlap when combining audience measurements across different device types (Pecjak; col. 3, lines 44-52).
Claim 20, which discloses a system, is analyzed with respect to the citations and/or rationale provided in the rejection of similar claim 3.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Kirillov et al., US 2016/0165277 in view of HSU et al., US 2016/0125471, Perez et al., US 2015/0046579, and Lessin et al., US 2014/0143048, and further in view of Kitts et al., US 2016/0037201.
Regarding claim 9, Kirillov in view of HSU, Perez, and Lessin discloses all the claimed limitations of claim 1, as well as the deduplicated audience metric is calculated using anonymized individual historical viewership (Kirillov; again based on at least individual viewership; page 2, paragraphs 23-24, and page 3, paragraph 37, and wherein this data can be anonymized by removing personally identifiable information; page 4, paragraph 37, and Perez; metrics/impressions relating to advertising; page 4, paragraph 44, and page 24, paragraph 198, and wherein deduplicated; Fig. 19, element 1914, and page 16, paragraph 128, and page 20, paragraph 163, and with obscured data; page 3, paragraph 38).
Kirillov in view of HSU, Perez, and Lessin does not explicitly disclose data that is obtained from a cleanroom.
In a related art, Kitts does disclose data that is obtained from a cleanroom (data via anonymizing from a clean room; page 2, paragraph 35, and Fig. 3A).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, Perez, Lessin, and Kitts by allowing the already disclosed anonymous data of Kirillov in view of HSU, Perez, and Lessin to be retrieved from a cleanroom, in order to provide an improved system and method for allowing advertisers to understand users’ behaviors through indirect use of raw data while maintaining privacy of the users and the data (Kitts; pages 1-2, paragraph 12).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kirillov et al., US 2016/0165277 in view of HSU et al., US 2016/0125471, Perez et al., US 2015/0046579, and Lessin et al., US 2014/0143048, and further in view of Wang, US 2016/0078032.
Regarding claim 11, Kirillov in view of HSU, Perez, and Lessin discloses all the claimed limitations of claim 10, as well as the first prediction is a prediction for individual views of the digital content (Kirillov; prediction with individual views; page 3, paragraphs 34-35, and page 5, paragraph 55, and pages 6-7, paragraph 72).
Kirillov in view of HSU, Perez, and Lessin does not explicitly disclose a time series prediction.
In a related art, Wang does disclose a time series prediction (estimation of view(s) based on time series data; page 3, paragraphs 31-32, and wherein times series data can be of predicted time series of views; page 5, paragraph 80).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, Perez, Lessin, and Wang by allowing certain data calculations to be included with the already performed predictions and operations of Kirillov, HSU, Perez, and Lessin, in order to provide an improved system and method for media scoring techniques for calculating view share and determining popularity of media (Wang; page 1, paragraph 2).
Claims 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Kirillov et al., US 2016/0165277 in view of HSU et al., US 2016/0125471, Perez et al., US 2015/0046579, and Lessin et al., US 2014/0143048, and further in view of Emans et al., US 2014/0196081.
Regarding claim 14, Kirillov in view of HSU, Perez, and Lessin discloses all the claimed limitations of claim 1, as well as the targetable digital audience segment (Kirillov; creation of promotional campaigns for use with sponsored content segments; page 1, paragraph 13, and page 4, paragraphs 43-44, and for use in a programmatic advertising system; page 4, paragraph 43, HSU; generation, and segments based on the particular data; page 8, paragraphs 83 and 85-86, and Perez; generating/creating; page 4, paragraph 37, and targeted advertising based on the data; page 6, paragraph 70, and page 7, paragraph 74, and with additionally determined opportunities to serve ads to a target user/audience; page 4, paragraph 39, and targeting markets with future, i.e. generated, advertisement opportunities; page 3, paragraph 40).
Kirillov in view of HSU, Perez, and Lessin does not explicitly disclose obtaining one or more inputs associated with placing an advertisement from an advertiser via a user interface based on data;
determining an allocation for the advertisement based on the one or more inputs; and
automatically providing the allocation to the advertiser.
In a related art, Emans does disclose obtaining one or more inputs associated with placing an advertisement from an advertiser via a user interface and based on viewership (can input campaign type goals and parameters for advertisement placing; page 9, paragraph 77, and Fig. 4, and wherein with at least inputs to a user interface; page 4, paragraph 40, and page 9, paragraph 75, and wherein based on viewership; page 9, paragraph 76);
determining an allocation for the advertisement based on the one or more inputs (can determine potential placements in relation to available advertising placements and the user inputs; page 9, paragraphs 77-78, and Fig. 4); and
automatically providing the allocation to the advertiser (once placements are determined they can be provided for approval, and then provided, i.e. automatically, for advertisement placements to be performed; page 9, paragraphs 77-79, and Fig. 4).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the prior art of Kirillov, HSU, Perez, Lessin, and Emans by allowing advertisement interfaces and placements to be provided with the already disclosed determinations and targeting operations of Kirillov in view of HSU, Perez, and Lessin, in order to provide an improved system and method for providing an interface for developing and optimizing a media placement plan for an advertising campaign (Emans; page 1, paragraph 4).
Regarding claim 15, Kirillov in view of HSU, Perez, Lessin, and Emans discloses providing pricing options associated with the allocation to the advertiser (Emans; system can provide pricing information associated with the advertisements; page 14, paragraph 115, and Fig. 11, and can also allow provision of budgeting constraints, i.e. other pricing options; page 9, paragraph 77, and page 16, paragraphs 136-138, and Fig. 13).
Regarding claim 16, Kirillov in view of HSU, Perez, Lessin, and Emans discloses receiving an advertising confirmation with respect to the allocation from the advertiser (Emans; approval, i.e. confirmation of the proposed placement(s); page 3, paragraph 35, and page 4, paragraph 39, and page 9, paragraph 78, and can also provide placement verification; page 10, paragraph 80); and
scheduling the advertisement to the allocation (Emans; advertisement placements performed; page 4, paragraph 39, and page 9, paragraphs 77-79, and Fig. 4, and wherein can be related to specific schedule of the advertisements; pages 9-10, paragraph 79, and page 11, paragraph 87, ad Fig. 7).
Regarding claim 17, Kirillov in view of HSU, Perez, Lessin, and Emans discloses the one or more inputs include at least one of hard constraints, soft constraints, flight times, and budget (Emans; with at least budgeting constraints; page 9, paragraph 77, and page 16, paragraphs 136-138, and Fig. 13).
Conclusion
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/RANDY A FLYNN/Primary Examiner, Art Unit 2424