Ne 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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claim 1 is directed to a computer-implemented method, comprising: a series of steps, and is therefore directed to a process, which is one of the four statutory categories.
Step 2A, Prong One:
Claim 1 recites the limitations:
identifying other requests to generate other dynamic objects through the object placement in response to the intent signal, wherein the other requests indicate other resource amounts for the other requests;
detecting in real-time the intent signal, wherein the intent signal is detected in real-time in response to user access to the network object;
and generating the dynamic object, wherein the dynamic object is generated using the set of assets, and wherein the dynamic object is generated through the object placement.
All of which can be performed in the human mind through observation, evaluation, judgement and opinion, with the aid of pen and paper, and are therefore reciting a mental process.
Accordingly, claim 1 recites a judicial exception (i.e., an abstract idea).
Step 2A, Prong Two
The additional elements recited in claim 1 include:
receiving a request to generate a dynamic object through an object placement in response to an intent signal, wherein the request indicates a resource amount allocated for the request, and wherein the object placement is implemented through a network object;
obtaining a set of assets corresponding to the dynamic object, wherein the set of assets are obtained as a result of the resource amount allocated for the request being greater than the other resource amounts;
Regarding the additional elements (i) and (ii), the limitations recited amounts to the insignificant extra-solution activity of mere data gathering, as it is merely gathering the information used by the judicial exception, which is not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(g).
Step 2B:
Regarding the additional elements (i) and (ii), the limitation recited is insignificant extra-solution activity which amounts to necessary data gathering. Further, the additional elements are transmitting data over a network, which have been identified by the courts as well-understood, routine, and conventional activity. See MPEP 2106.05(d). The courts have found adding insignificant extra-solution activity and well-understood, routine and conventional activity is not enough to amount to significantly more than the recited judicial exception. See MPEP 2106.0S(a) and 2106.0S(g).
The combination of these additional elements amounts to a method comprising steps which can
be performed mentally comprising steps of insignificant extra-solution and well-understood, routine and conventional activity.
Therefore, the additional elements, when considered individually and in combination, fail to add an inventive concept to the claim.
Consequently, claim 1 as a whole does not amount to significantly more than the recited judicial exceptions and the claim is not eligible.
Claims 2-7 are dependent on claim 1, and therefore inherits the same judicial exceptions recited in claim 1. Claim 2 recites the limitation “and customizing the dynamic object according to the user access,”. Since a person would still be able to perform the steps specified in the limitation recited by claim 2 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 2 is still reciting a mental process. Claim 3 recites the limitation “assigning a pairing of the object placement to the intent signal to a requesting system associated with the request as a result of the resource amount allocated for the request being greater than the other resource amounts, wherein the pairing is assigned to the requesting system subject to an expiration date after which the pairing is made available to other systems.”. Since a person would still be able to perform the steps specified in the limitation recited by claim 3 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 3 is still reciting a mental process. Claim 4 recites the limitation “wherein the object placement is associated with one or more application programming interfaces (APIs) that are exposed when the network object is accessed, and wherein when the user access is performed,”. Since a person would still be able to perform the steps specified in the limitation recited by claim 4 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 4 is still reciting a mental process. Claim 5 recites the limitation “wherein the set of assets are obtained as a result of the resource amount allocated for the request being greater than a reserve resource amount designated for the object placement and the intent signal.”. Since a person would still be able to perform the steps specified in the limitation recited by claim 5 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 5 is still reciting a mental process. Claim 6 recites the limitation “wherein the set of assets are obtained as a result of a number corresponding to the other requests being greater than a minimum number of requests designated for the object placement and the intent signal.”. Since a person would still be able to perform the steps specified in the limitation recited by claim 6 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 6 is still reciting a mental process. Claim 7 recites the limitation “wherein the set of assets include configuration information corresponding to the object placement, and wherein when the dynamic object is generated, the configuration information is used to configure the object placement for the dynamic object.”. Since a person would still be able to perform the steps specified in the limitation recited by claim 7 in the human mind, through observation, evaluation, judgement and opinion, with the aid of pen and paper, the limitation of claim 7 is still reciting a mental process.
Claim 2 recites “dynamically training in real-time a machine learning algorithm to customize dynamic objects according to received user data, wherein the machine learning algorithm is dynamically trained in real-time using sample user data and feedback corresponding to dynamic objects generated according to the sample user data;” and “the dynamic object is customized by the machine learning algorithm based on the user access.” These additional elements amount to mere instructions to implement the abstract idea recited earlier, which is equivalent to adding the words “apply it” to the recited judicial exception. See MPEP 2106.05(h). This additional element is not indicative of integration into a practical application Even when considered in combination with the additional elements of claim 1, the additional elements comprise mere instructions to apply the exception and insignificant extra-solution activity, which are not indicative of integration into a practical application. Even when considered in combination with the additional elements of claim 1, the additional elements do not provide an inventive concept and do not amount to significantly more than the recited judicial exceptions. Thus, claim 2 is ineligible. Claims 3,5-7 do not recite any additional elements beyond those recited in claim 1. Accordingly, for the same reasons presented with respect to claim 1, the additional elements are not indicative of integration into a practical application, nor do they amount to significantly more than the recited judicial exceptions. Thus, claim X is not eligible. Claim 4 recites “the APIs are used to detect the intent signal.” This additional element amount to mere instructions to implement the limitations which can be performed in the human mind on a computer, which is not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). This additional element is not indicative of integration into a practical application Even when considered in combination with the additional elements of claim 1, the additional elements comprise mere instructions to apply the exception and insignificant extra-solution activity, which are not indicative of integration into a practical application. Even when considered in combination with the additional elements of claim 1, the additional elements do not provide an inventive concept and do not amount to significantly more than the recited judicial exceptions. Thus, claim 4 is ineligible.
Claim 8 recites A system, comprising: one or more processors; and memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:: perform the steps of the method of claim 1. Thus, for the same reasons presented with respect to claim 1, claim 8 is rejected because the claimed invention is directed to an abstract idea without significantly more.
Claims 9-14 recite substantially the same limitations as those recited in claims 2-7, respectively, applied to the apparatus of claim 8. Thus, for the same reasons presented with respect to claims 2-7, claims 9-14 are directed to an abstract idea without significantly more and are not eligible.
Claim 15 recites A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to: perform the steps of the method of claim 1. Thus, for the same reasons presented with respect to claim 1, claim 15 is rejected because the claimed invention is directed to an abstract idea without significantly more.
Claims 16-21 recite substantially the same limitations as those recited in claims 2-7, respectively, applied to the apparatus of claim 8. Thus, for the same reasons presented with respect to claims 2-7, claims 16-21 are directed to an abstract idea without significantly more and are not eligible.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3-4, 7-8, 10-11, 14-15, 17-18, 21 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Yan et. al. (US 20140344073 A1), hereinafter Yan.
Regarding Claim 1, Yan recites:
A computer-implemented method, comprising:
receiving a request to generate a dynamic object through an object placement in response to an intent signal, wherein the request indicates a resource amount allocated for the request, and wherein the object placement is implemented through a network object; (see e.g., page [04], paragraph [0036], “For example, advertisements might be maintained and stored remote from the advertisement selection engine 206. In such a case, when a user enters a search via the user device 202, the advertisement selection engine 206 can directly place a call or request to the advertiser device 204 with the query from the user to request an advertisement(s) to present and/or a corresponding bid(s).”) Presenting the ad would consist of the ‘generation’ of a ‘dynamic object’, as can be seen later.
identifying other requests to generate other dynamic objects through the object placement in response to the intent signal, wherein the other requests indicate other resource amounts for the other requests; (see e.g., page [04], paragraph [0036], “Accordingly, the real-time bidding component 218 of the advertisement selection engine 206 performs a call out to the real-time bidding agent 214 of the advertiser device 204 when a search query is received. In response, the real-time bidding agent 214 of the advertiser device 204 returns an appropriate advertisement(s) and corresponding bid(s) to be used in the auction for advertisements to be displayed in association with the search query.”) This shows that the above process is repeated for any applicable ads.
obtaining a set of assets corresponding to the dynamic object, wherein the set of assets are obtained as a result of the resource amount allocated for the request being greater than the other resource amounts; (see e.g., page [07], paragraph [0059], “In such a case, the real-time bidding component 218 might provide the adjusted advertisement bid of two cents to the auctioning component 220 for participation in the auction. Now assume that the advertisement associated with the two cent bid is successful in the auction. The real-time bidding component 218 could provide the modified advertisement for transmission to a user. In some implementations, the real-time bidding component might communicate the modified advertisement to the user device (e.g., after the advertisement is selected in the advertisement auction). In other implementations, the real-time bidding component might provide the advertisement to the auctioning component 220 (e.g., at auction time or after advertisement selection) for provision to the user device, if applicable.”)
detecting in real-time the intent signal, wherein the intent signal is detected in real-time in response to user access to the network object; (see e.g., page [06], paragraph [0050], “Upon receiving a request for a webpage and/or search results associated with a particular search query, the advertisement selecting component 216 selects one or more advertisements deemed relevant, for example, to the webpage and/or search query.”) The intent signal is the context data that is provided to the advertisement selecting component. (see e.g., page [08], paragraph [0069], “At block 508, the advertisement context data is used to determine to provide a real-time advertisement. For example, based on the search query, it may be determined to modify the advertisement title to be more relevant to the search query. Thereafter, the real-time bid and the real-time advertisement are provided for participation in an advertisement auction, as indicated at block 510.”) This shows the search query also being used to specifically modify text shown on the advertisement to be more relevant to the search query.
and generating the dynamic object, wherein the dynamic object is generated using the set of assets, and wherein the dynamic object is generated through the object placement. (see e.g., page [07], paragraph [0059], “In such a case, the real-time bidding component 218 might provide the adjusted advertisement bid of two cents to the auctioning component 220 for participation in the auction. Now assume that the advertisement associated with the two cent bid is successful in the auction. The real-time bidding component 218 could provide the modified advertisement for transmission to a user. In some implementations, the real-time bidding component might communicate the modified advertisement to the user device (e.g., after the advertisement is selected in the advertisement auction). In other implementations, the real-time bidding component might provide the advertisement to the auctioning component 220 (e.g., at auction time or after advertisement selection) for provision to the user device, if applicable.”) This shows the dynamic object (the [potentially modified] advertisement) being sent to the user device for placement. “the dynamic object is generated through the object placement”, as is stated in the claim, is being interpreted as the advert having been customized in real-time, as described earlier (e.g., the dynamic object is generated while placing or specifically for the placement of the dynamic object) This was shown in an earlier limitation.
Regarding claim 3, Yan recites:
The computer-implemented method of claim 1, further comprising: assigning a pairing of the object placement to the intent signal to a requesting system associated with the request as a result of the resource amount allocated for the request being greater than the other resource amounts, wherein the pairing is assigned to the requesting system subject to an expiration date after which the pairing is made available to other systems. (see e.g., page [07], paragraph [0058], “In some embodiments, the real-time bidding component 218 might be configured to time out when the real-time bidding agent does not respond within a predetermined time period. In this regard, the advertisement auction can proceed when the bidding agent fails to respond in the specified time period.”) This shows the expiration time for a bid (which would continue the process if the winner doesn’t respond). (see also e.g., page [07], paragraph [0059], “Now assume that the advertisement associated with the two cent bid is successful in the auction. The real-time bidding component 218 could provide the modified advertisement for transmission to a user. In some implementations, the real-time bidding component might communicate the modified advertisement to the user device (e.g., after the advertisement is selected in the advertisement auction). In other implementations, the real-time bidding component might provide the advertisement to the auctioning component 220 (e.g., at auction time or after advertisement selection) for provision to the user device, if applicable.”) This shows that the object (including the modifications associated with the intent signal) are sent together as a result of the winning bid to the user.
Re. claim 4, Yan recites:
The computer-implemented method of claim 1, wherein the object placement is associated with one or more application programming interfaces (APIs) that are exposed when the network object is accessed, and wherein when the user access is performed, the APIs are used to detect the intent signal. (see e.g., page [004], paragraph [0035], “To input advertisement data, advertisement preferences, and/or real-time bidding preferences, a web browser or application on the advertiser device 204 (or other computing device) may be used. An advertiser can input advertisement data, advertisement preferences, and/or real-time bidding preferences into advertiser device 204 in any number of manners, for example, using an advertising user interface that enables an advertiser to input, provide, or select advertising data.”) This shows a user interface (a specialized access point interface) as one of the things that can provide advertisement data or preferences to the system. (see also e.g., page [01], paragraph [0005], “As such, based on the context associated with the received query, the advertiser can determine whether to modify or adjust a previously submitted advertisement or corresponding bid for participation in the advertisement auction. ”) This shows the context received from the query is exposed to the advertiser when the user accesses the website, and is provided to the advertiser so that the algorithm may choose how to proceed.
Regarding claim 7, Yan recites:
The computer-implemented method of claim 1, wherein the set of assets includ0000 dynamic object is generated, the configuration information is used to configure the object placement for the dynamic object. (see e.g., page [05], paragraph [0042], “Such a real-time advertisement might be a new advertisement that has not been previously provided, a modified advertisement of one that has been previously provided (e.g., via the advertisement settings component 212) to the advertisement selection engine 206, or advertisement data that includes data or content to include along with or supplement an advertisement that has been previously provided to the advertisement selection engine 206. Such a modification or supplement may include a modification or addition of text (e.g., advertisement title, advertisement caption or description, a display URL, a destination URL, etc.), images, formatting (e.g., highlighting, coloring, etc.), and/or the like.”)
Regarding claim 8, Yan recites A system, comprising:one or more processors; and memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to: perform the method of claim 1. As such, claim 8 is rejected as being anticipated by Yan for the same reasons presented with respect to claim 1.
Claims 10, 11, and 14 recite substantially the same limitations as claims 3, 4, and 7, applied to the system of claim 8. As such, claims 10, 11, and 14 are rejected as being anticipated by Yan for the same reasons presented with respect to claims 3, 4, and 7.
Regarding claim 15, Yan recites A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to: perform the method of claim 1. As such, claim 8 is rejected as being anticipated by Yan for the same reasons presented with respect to claim 1.
Claims 17, 18, and 21 recite substantially the same limitations as claims 3, 4, and 7, applied to the non-transitory computer readable storage medium of claim 8. As such, claims 17, 18, and 21 are rejected as being anticipated by Yan for the same reasons presented with respect to claims 3, 4, and 7.
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 2,9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Yan as described above, and further in view of Xiao (“Research on Machine learning methods for intelligent decision problems”, 2019), hereinafter Xiao.
Regarding Claim 2, Yan teaches:
The computer-implemented method of claim 1, further comprising: dynamically training in real-time a [algorithm] to customize dynamic objects according to received user data, and customizing the dynamic object according to the user access, wherein the dynamic object is customized by the [algorithm] based on the user access. (see e.g., page [005], paragraph [0043], “In operation, the real-time bidding agent 214 can assess the advertisement selected for participation in the advertisement auction in combination with any available advertisement context (e.g., search query, user attributes, etc.) and determine whether and to what extent to provide a real-time bid(s) and/or real-time advertisement(s). The real-time bidding agent 214 may employ any number or manner of rules or algorithms to make such a decision. Such a determination might be based on, for instance, user attributes, the content query (e.g., keyword(s)), intent of the query (e.g., to purchase or acquire), value to the advertiser, time and/or date of query/auction, budget constraints of the advertiser, and/or the like.”) (see also e.g., page [08], paragraph [0069], “At block 508, the advertisement context data is used to determine to provide a real-time advertisement. For example, based on the search query, it may be determined to modify the advertisement title to be more relevant to the search query. Thereafter, the real-time bid and the real-time advertisement are provided for participation in an advertisement auction, as indicated at block 510.”) This shows an algorithm customizing the dynamic object according to the received user data and/or the content of the page the user is accessing.
Yan fails to explicitly teach:
A machine learning algorithm
wherein the machine learning algorithm is dynamically trained in real-time using sample user data and feedback corresponding to dynamic objects generated according to the sample user data;
However, Xiao teaches:
A machine learning algorithm
wherein the machine learning algorithm is dynamically trained in real-time using sample user data and feedback corresponding to dynamic objects generated according to the sample user data;
(see e.g., page [595], paragraph [04], “Supervised learning refers to the training experience clearly telling the correct results. Just as people learn diagnostic technology through known cases, computers need to learn to have the ability to recognize all kinds of things and phenomena. […] “To sum up, if we only evaluate the behavior of the program, the program will make the behavior that is more likely to be evaluated positively. Enhanced learning is widely used in intelligent control robots and analysis and prediction.”) This shows a machine learning algorithm’s training method, which is trained as it performs the function while receiving feedback, and as described in the paragraph before, is a subgroup of “inductive learning (i.e. learning outcomes from training samples.)” (see page [595], paragraph [03])
Yan and Xiao are considered to be analogous art to the claimed invention as they are
reasonably pertinent to the problem faced by the inventor of selecting an algorithm to make quick decisions. Therefore, it would have been obvious to one of ordinary skill in the art that the system lacking a specific decision-making algorithm taught by Yan could include a machine learning algorithm as taught by Xiao. Utilizing machine learning would provide decisions “that [are] more likely to be evaluated positively.” (see e.g., page [595], paragraph [04])
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yan as applied to claims above, and further in view of Great Expectations et al (“what is a reserve price at an auction?”, April 2019, Great Expectations Auction & Auto Brokerage), hereinafter Great Expectations.
Re. claim 5, Yan teaches:
The computer-implemented method of claim 1,
Yan fails to explicitly teach:
wherein the set of assets are obtained as a result of the resource amount allocated for the request being greater than a reserve resource amount designated for the object placement and the intent signal.
However, Great Expectations teaches:
wherein the set of assets are obtained as a result of the resource amount allocated for the request being greater than a reserve resource amount designated for the object placement and the intent signal. (see e.g., page [01], paragraph [05-07], “Here’s an example of a reserve price: A seller is selling a vehicle at auction. He sets a reserve price of $6,000. The auctioneer opens the bidding at $4,000 and bidders work their way up until the price is $5,900. Nobody wants to bid more than $5,900 for the vehicle. The auctioneer removes the vehicle from the auction because the reserve price has not been met.”) This shows a reserve price and how it functions in an auction, which, once matched with the context provided by Yan (i.e., an auction selling ad space), would follow the assets related to the advertisement only being sent to the user once a reserve price designated was met by one of the bids.
Yan and Great Expectations are considered to be analogous art to the claimed invention as they are reasonably pertinent to the problem faced by the inventor of deciding if someone has successfully completed (and won) a bid in an auction. Therefore, it would have been obvious to one of ordinary skill in the art that the method to auction off advertisement space as taught by Yan could include a minimum price to sell the ad space in the auction as taught by Great Expectations. Doing so would “protect the owner of the [ad space] from having to part with it for less money than he or she wants to” (see e.g., page [01], paragraph [02-03]).
Claims 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Yan as applied to claims above, and further in view of ComprehensiveUsernam et al. ("Minimum number of people required to get the market price out of an auction within 5% margin of error", March 2019, Reddit), hereinafter Usernam.
Regarding claim 6, Yan teaches:
The computer-implemented method of claim 1,
Yan fails to explicitly teach:
wherein the set of assets are obtained as a result of a number corresponding to the other requests being greater than a minimum number of requests designated for the object placement and the intent signal.
However, Usernam teaches:
wherein the set of assets are obtained as a result of a number corresponding to the other requests being greater than a minimum number of requests designated for the object placement and the intent signal. (see e.g., page [01], paragraph [03-08], “I'm building an ebay-esque webapp and I'm wondering how many participants at the various auctions I need for the platform to work.
Ideas: Minimum number of participants to get an auction to work:
2 people, then the out-bidding mechanism starts to work, but obviously the willingness-to-pay will have extreme outliers.
Optimal number (whereas optimal means the market price will likely come out):
That's the question. If we assume that the willingness-to-pay follows a normal distribution, then how do I proceed? Is this a likely assumption?”) This shows an understanding that at a bare minimum, there needs to be 2 people to have an auction function. (if an auction only has one person, it is in effect a sale that the buyer has control over the price rather than the seller), and that the bidding mechanism would only work when 2 or more people are gathered to bid. This also shows that, in order to be confident that a return on the sale is made, there is an optimal number that should be aimed for before bidding begins.
(see also e.g., page [02], paragraph [03-04] (reply by mfb-), “If you assume the maximum people want to pay follows a normal distribution then you need the expectation value for the second highest willingness-to-pay. You should get that with a double integral. Here are some formulas[link to math stackexchange]. As a good approximation (which leads to a simpler calculation) you can look for the point where your expected number of people willing to pay more is 1.5 or something like that.”) This provides 2 ways to solve the problem, with the discussion continuing to provide other methods to solve for when bidding should be allowed for any given object with a market price and data corresponding with said market price.
Yan and Usernam are considered to be analogous art to the claimed invention as they are
reasonably pertinent to the problem faced by the inventor of deciding when active bidding is allowed to begin in an auction. Therefore, it would have been obvious to one of ordinary skill in the art that the method to auction off advertisement space as taught by Yan could include a minimum attendance to begin the auction as taught by Usernam. Using one of Usernam’s suggested formulas would allow for the auctioneer to be confident (up to a margin of error they are comfortable with) that they would “get at least the market price out of it” (see e.g., page [001], paragraph [02])
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Connor Imiola Blackburn whose telephone number is (571)272-6547. The examiner can normally be reached M-Th 7-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kevin Young can be reached at (571) 270 - 3180. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/C.I.B./Examiner, Art Unit 2194 /KEVIN L YOUNG/Supervisory Patent Examiner, Art Unit 2194
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