DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) the following limitations that are considered to be abstract ideas:
Claims 1 and 11
obtaining, one or more configuration inputs indicating a total amount, a plurality of placement goal objectives, and one or more priority values corresponding to the one or more placement goal objectives;
obtaining, historical targeting configuration data for a plurality of prior data transmissions;
for each prior data transmission, generating, a set of goal performance metrics for the placement goal objectives based upon the historical targeting configuration data of the prior data transmission;
generating, a blocklist comprising a set of one or more online resources having a goal objective value of a corresponding goal objective that fails to satisfy a threshold for the goal objective; and
generating, a placement instruction for placing content objects for at least one online resource in accordance with the blocklist.
Claim 11
obtaining, one or more configuration inputs indicating a total value amount, one or more placement goal objectives, and
one or more priority values corresponding to the one or more goal objectives; obtaining, a plurality of samples of a plurality of sample target requests based upon a set of placement target criteria, each sample including target request data of a sample target request for a sample online resource satisfying the target criteria;
for each sample, generating, a set of goal performance metrics for the plurality of placement goal objectives based upon historical targeting configuration data of prior content placement;
for each sample, obtaining, dual variables for an optimization function based upon the goal performance metrics corresponding to an optimal sample value for the sample online resource corresponding to the sample; and
generating, an optimal target value for an incoming target request indicating an online resource using the dual variables of the optimization function.
The limitations of independent claims 1 and 11 as detailed above, as drafted, falls within “Certain Methods of Organizing Human Activity” specifically commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and/or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The applicant’s claims are directed to collecting targeting information, evaluating historical performance of online resources, determining acceptable placement locations, and generating placement instructions. Accordingly, the claims recite an abstract idea
This judicial exception is not integrated into a practical application. In particular the claims recite the additional elements of:
computer
Distributed network
The aforementioned additional generic computing elements perform the steps of the claims at a high level of generality (i.e. As a generic medium performing generic computer function of obtaining, generating and transmitting) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer, or to any other technology, or technical field. Their collective functions merely provide generic computer implementation.
Thus, taken individually and in combination, the additional elements do not amount to
significantly more than the above-identified judicial exception (the abstract idea).
The dependent claims 2-10 and 12-20 appear to merely further limit the abstract and as such, the analysis of dependent claims 2-10 and 12-20 results in the claims “reciting” an abstract idea. For example, claims merely further define or limit parameters, blocklist, performance metrics, etc. The claims the claims do not recite additional elements that integrate the exception into a practical application the additional elements do not amount to an inventive concept (significantly more) other than the above-identified judicial exception (the abstract idea).
Thus, based on the detailed analysis above, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-3, 5, 7,9 and 10 is/are rejected under 35 U.S.C. 102(a)(1)as being anticipated by Els et al. (US 10, 002, 368)
Claim 1: Els discloses a method for multi-objective evaluation for computer-implemented data transmission within a distributed network environment, the method comprising:
obtaining, by a computer, one or more configuration inputs indicating a total amount, a plurality of placement goal objectives and one or more priority values corresponding to the one or more placement goal objectives; ( see Col3 lines 40-47) RTB environment in a manner that maximizes the campaign goals at market efficient prices and that meets the required impression quota. Campaign goals may take the form of: a particular demographic audience, a desired CTR, a desired cost per click, a video view rate, a number of online purchases/actions, a desired cost per purchase/action, offline sales, or maximize the rate at which any target event occurs and Col 9 lines 60-65, 59) If too few impressions are being won, the system may increase the bid price to a maximum acceptable point, or lower the target score iteratively until impressions are won at the desired rate to meet that daily impression quota.
obtaining, by the computer, historical targeting configuration data for a plurality of prior data transmissions; (see Col.5 lines 5 – 17, impression and various other forms of information from all known campaigns are grouped together into advertisement placement definitions. Other forms of information may, for instance, include cross campaign placement comparisons that reveal whether certain advertisement sizes are more effective than others. And Col 14 lines 6-11, placements data are used to identify similar and related advertisement campaigns and exploit the related placements data by relying more on impression history of similar campaigns, thus weighing their ratings more than dissimilar or unrelated campaigns.)
for each prior data transmission, generating, by the computer, a set of goal performance metrics for the placement goal objectives based upon the historical targeting configuration data of the prior data transmission; (Col. 5 lines 55-63) the performance of each advertisement placement is determined based on standard user-based recommendation, the performance metrics are standardized for each campaign. )
generating, by the computer, a blocklist comprising a set of one or more online resources having a goal objective value of a corresponding goal objective that fails to satisfy a threshold for the goal objective and generating, by the computer, a placement instruction for placing content objects for at least one online resource in accordance with the blocklist. (Col. 5 lines 20-45, Thus, each campaign is associated with its own minimum and maximum levels. At 104, advertisement placements from each on-going campaign that do not meet a minimum performance level are removed. At 105, advertisement placements that have suspiciously high performance metrics are also removed as they may be indicative of non-human activity, such as those performed by spiders/crawlers that generate fake clicks. At 106, new advertisement placements are added to each on-going campaign based on their aggregate performance score (determined at 101). At 107, some proportion of placements that are completely new to the system (e.g., no performance information from previous campaigns) may be added to the better performing, on-going campaigns. This allows the learning of performance information regarding speculative advertisement placements. (29) In addition to the selection process illustrated in FIG. 1, each campaign may be associated with specified “white lists” or “black lists” that may affect the scoring and ranking of advertisement placements. A white list may refer to a list of domains that are adequate for advertisement placements. This could be a list from a client, an internal list, or a list based on domain categories. A black list may refer to a list of sites that are excluded from the server because they that have deemed undesirable for a campaign)
Claim 2: Els discloses the method of claim 1, further comprising receiving, by the computer, user input specifying a minimum acceptable performance threshold for each placement goal objective. (Col 5 lines 15-20, col. 11 lines 40-45)
Claim 3: Els discloses the method of claim 1, wherein generating the blocklist includes analyzing, by the computer, historical performance data for each online resource to identify online resources that repeatedly fail to satisfy the threshold for at least one placement goal objective. (Col. 5 lines 20-45 and Col 16 lines 25-35)
Claim 5: Els discloses the method of claim 1, wherein generating the placement instruction comprises excluding, by the computer, any online resource included in the blocklist from eligibility for receiving content objects. (Col5 lines 35-45)
Claim 7: Els discloses the method of claim 1, wherein the set of goal performance metrics includes at least one of a cost-per-click, a click-through rate, an engagement rate, or a conversion rate. (Col 3 lines 43 -50)
Claim 9: Els discloses the method of claim 1, wherein obtaining the historical targeting configuration data includes retrieving, by the computer, placement-level data for each prior data transmission from one or more databases. (Col 5 lines 15-30)
Claim 10: Els discloses the method of claim 1, further comprising transmitting, by the computer, the placement instruction to a placement engine configured to execute real-time targeting for data transmission. (Col 11 lines 52-60)
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 4, 6, is/are rejected under 35 U.S.C. 103 as being unpatentable over Els et al. (US 10, 002, 368) in view of Desikan et al. (US 2007/0005417)
Claim 4: Els discloses the method of claim 1, but does not disclose further comprising blocking, by the computer, at least one placement instruction for at least one content object associated with at least one online resource included in the blocklist.
However, Desikan discloses blocking, by the computer, at least one placement instruction for at least one content object associated with at least one online resource included in the blocklist. [0047, 0055, 0056]
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify, Els to include blocking, by the computer, at least one placement instruction for at least one content object associated with at least one online resource included in the blocklist, in order to increase revenue for advertisers by placing advertisements where they are relevant and high traffic areas. ([0041, 0065, 0072], Desikan)
Claim 6: Els discloses the method of claim 1, but does not explicitly disclose further comprising updating, by the computer, the blocklist in response to real-time performance data received during execution of the targeted placement.
However Desikan comprising updating, by the computer, the blocklist in response to real-time performance data received during execution of the targeted placement. [0089]
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify, Els to include updating, by the computer, the blocklist in response to real-time performance data received during execution of the targeted placement in order to improve the quality of the websites. ([0088 and 0089], Desikan)
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Els et al. (US 10, 002, 368) in view of Zabarauskas et al. (US2023/0117616)
Claim 8. Els discloses the method of claim 1, further comprising providing, but does not explicitly disclose by the computer, a user interface including the blocklist for display at a user device, the user interface configured to obtain an instruction for inclusion of an online resource in the blocklist. However Zabarauskas discloses a user interface including the blocklist for display at a user device, the user interface configured to obtain an instruction for inclusion of an online resource in the blocklist.[0053 and 0055]
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify, Els to include a user interface including the blocklist for display at a user device, the user interface configured to obtain an instruction for inclusion of an online resource in the blocklist. in order to assist a user in configuring settings. ([0055], Zabarauskas)
Claim(s) 11 - 20, is/are rejected under 35 U.S.C. 103 as being unpatentable over Agarwal et al. (US 2010/0114721) in view of Els et al. (US 10, 002, 368)
Claim 11: Els discloses a method for computer-implemented data transmission by optimizing on dual-variables in data transmission, the method comprising:
obtaining, by a computer, one or more configuration inputs indicating a total value amount, one or more placement goal objectives, and one or more priority values corresponding to the one or more goal objectives; ([0006], . A book rate value may be obtained for each of the impression pools of the inventory of online advertisement impressions, The objective function may be a weighted composite of maximizing the cost of unused inventory and proportionally allocating a set of impression pools which can supply advertisers' requests.)(equivalent to the goal objective)
obtaining, by the computer, a plurality of samples of a plurality of sample target requests based upon a set of placement target criteria, each sample including target request data of a sample target request for a sample online resource satisfying the target criteria; [0006] An inventory of online advertisement impressions may be grouped in impression pools according to attributes of the advertisement impressions and advertisers' requests for impressions targeting specific attributes may be received, claim 4 receiving a plurality of impression pools of a plurality of advertisement impressions; receiving a plurality of requests for a plurality of advertisement placements on a plurality of display properties) for each sample, obtaining, by the computer, dual variables for an optimization function based upon the goal performance metrics corresponding to an optimal sample value for the sample online resource corresponding to the sample; ([0006], an optimal price may be computed for each of the impression pools of the inventory of online advertisement impressions using dual values from an optimization program that allocates the advertisement impressions from the impression pools. I[0032], that a dual values associated with supply constraints from a primal solution of an optimization program applied to allocate advertisement impressions may be used to compute an optimal price for each of the impression pools. An allocation and pricing optimizer, for instance, may apply a non-linear program to allocate advertisement impressions for an objective functions and extract values of the dual variable of the supply constraint from the non-linear program solution.) and
generating, by the computer, an optimal target value for an incoming target request indicating an online resource using the dual variables of the optimization function ([0034, 0037 and claim 4 outputting the optimal price for each of the plurality of impression pools of the plurality of advertisement impressions computed using the dual values from the optimization program.) But does not explicitly disclose for each sample, generating, by the computer, a set of goal performance metrics for the plurality of placement goal objectives based upon historical targeting configuration data of prior content placement;
However Els discloses for each sample, generating, by the computer, a set of goal performance metrics for the plurality of placement goal objectives based upon historical targeting configuration data of prior content placement; (Col. 5 lines 55-63) the performance of each advertisement placement is determined based on standard user-based recommendation, the performance metrics are standardized for each campaign. )
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify, Els to include for each sample, generating, by the computer, a set of goal performance metrics for the plurality of placement goal objectives based upon historical targeting configuration data of prior content placement in order to increase the likelihood that traffic is increased and improve revenue. (Col 14 lines 5-15) Els
Claim 12: Agarwal discloses the method of claim 11, further comprising storing, by the computer, the dual variables in a non-transitory memory accessible to a placement engine for determining a next target value. [0005 and 0006]
Claim 13: Agarwal discloses the method of claim 11, wherein obtaining the plurality of samples comprises retrieving, by the computer, target request data from a real-time stream associated with a plurality of online resources. [0016 and 0024]
Claim 14: Agarwal discloses the method of claim 11, further comprising updating, by the computer, the set of dual variables in response to one or more updates to one or more performance metrics received during execution of the targeted placement. [0032]
Claim 15: Agarwal discloses the method of claim 11, but does explicitly disclose wherein the set of goal performance metrics includes at least one of an expected click-through rate, an expected engagement rate, an expected conversion rate, or an expected cost-per-click.
However Els discloses wherein the set of goal performance metrics includes at least one of an expected click-through rate, an expected engagement rate, an expected conversion rate, or an expected cost-per-click. (Col 3 lines 43 -50)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify, Els to include wherein the set of goal performance metrics includes at least one of an expected click-through rate, an expected engagement rate, an expected conversion rate, or an expected cost-per-click., in order to in order to find new placements that perform well and use them in popularity placement. Col. 14 lines 15-25) Els
Claim 16: Agarwal discloses the method of claim 11, further comprising transmitting, by the computer, the optimal target value to a placement engine configured to submit the target request for the incoming target request. [0005 and 0006]
Claim 17: Agarwal discloses the method of claim 11, wherein the optimization function includes a non-linear programming model configured to optimize on the plurality of placement goal objectives according to the priority values. [0025]
Claim 18: Agarwal discloses the method of claim 11, further comprising generating, by the computer, a report indicating the optimal target values and corresponding dual variables for a plurality of online resources. [0025 and 0026]
Claim 19: Agarwal discloses the method of claim 11, wherein obtaining the dual variables includes executing, by the computer, one or more machine-learning models, including at least one of a gradient-boosted tree, a support vector machine, or a neural network. [0026]
Claim 20: Agarwal discloses the method of claim 11, further comprising providing, by the computer, a user interface including the optimal target value for display at a user device, the user interface configured to obtain an adjustment input to at least one priority value for the placement goal objectives. [0033]
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Merriman et al. (US 2010/0023392) - Methods and apparatuses for targeting the delivery of advertisements over a network such as the Internet are disclosed. Statistics are compiled on individual users and networks and the use of the advertisements is tracked to permit targeting of the advertisements of individual users. In response to requests from affiliated sites, an advertising server transmits to people accessing the page of a site an appropriate one of the advertisement based upon profiling of users and networks.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DARNELL A POUNCIL whose telephone number is (571)270-3509. The examiner can normally be reached Monday - Friday 10:00 - 6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ilana Spar can be reached at (571) 270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/D.A.P/Examiner, Art Unit 3622
/ILANA L SPAR/Supervisory Patent Examiner, Art Unit 3622
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