DETAILED ACTION
The following is a first office action upon examination of application number 18/650785. Claims 1-20 are pending in the application and have been examined on the merits discussed below.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
(Step 1) Claims 1-15 are directed to a system comprising one or more processors; thus the system comprises a device or set of devices, and therefore, is directed to a machine which is a statutory category of invention. Claims 16-19 are directed to a method; thus these claims are directed to a process, which is one of the statutory categories of invention. Claim 20 is directed to a non-transitory computer-readable medium, which is a manufacture, and this a statutory category of invention.
(Step 2A) The claims recite an abstract idea instructing how to simulate a content delivery platform, which is described by claim limitations reciting:
accessing historical data generated from a real-world execution of a content delivery platform for a particular market that is defined at least in part by a prior time interval;
determining a set of simulation configurations, each simulation configuration representing a deviation to the real-world execution of the content delivery platform;
generating a simulation execution of the content delivery platform for the particular market using the set of simulation configurations; and
recording outcomes of the simulation execution.
The identified limitations in the claims describing simulating a content delivery platform (i.e., the abstract idea) fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, which covers fundamental economic practices and marketing activities. Dependent claims 2-15 and 17-19, recite limitations that further narrow the abstract idea; therefore, these claims are also found to recite an abstract idea.
This judicial exception is not integrated into a practical application because additional elements such as the one or more processors; memory to store instructions; and wherein the one or more processors execute the instructions to perform operations in claim 1; the one or more processors of a computer system in claim 16; and the non-transitory computer-readable medium that stores instructions, which when executed by one or more processors of a computer system, cause the computer system to perform operations in claim 20, do not add a meaningful limitation to the abstract idea since these elements are only broadly applied to the abstract ideas at a high level of generality; thus, none of recited hardware offers a meaningful limitation beyond generally linking the abstract idea to a particular technological environment, in this case, implementation via a processor/computer. Accordingly, these additional element do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
(Step 2B) The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration of the abstract idea into a practical application, the hardware additional elements amount to no more than mere instructions to apply the exception using a generic computer component (see Spec. [0083]). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
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) 1-13 and 16-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2016/0283974 (Sodomka).
As per claim 1, Sodomka teaches: a computer system comprising: one or more processors; a memory to store instructions; wherein the one or more processors execute the instructions to perform operations comprising: ([0047] … software module is implemented with a computer program product comprising a computer-readable medium containing computer program code, which can be executed by a computer processor for performing any or all of the steps, operations, or processes described.)
accessing historical data generated from a real-world execution of a content delivery platform for a particular market that is defined at least in part by a prior time interval; ([0015] … simulates advertisement selection for a set of historical ad queries [0027] … The ad query store 210 thus records ad queries previously received and served by the advertising system 100. .. Each ad query represents a request from a client device for an advertisement and is associated with a user of the client device. The ad query may indicate, for example, that a request was received from a specific user at a specific time and may represent one or more advertisement slots to be provided to the client device 110. [0029] … original selection of advertising results that were selected when ads were served by the advertising system 100 may be stored in the ad result store 220 [0022] … The advertising campaign may specify a budget, duration, bid amount, bid frequency, targeting criteria … duration indicates a length of time for the advertising [0031] … simulation module 225 may also determine the competing advertisers for an ad query. In one embodiment, the competing advertisers are identified in the ad query store 210 as the advertisers that previously bid on the ad query when the ad query was originally provided an advertisement by advertising system 100)
determining a set of simulation configurations, each simulation configuration representing a deviation to the real-world execution of the content delivery platform; ([0003] … An advertiser or operator of the adverting system may wish to know the performance of advertisements under different conditions from the conditions under which ads were originally served [0005] … conditions are modified during the simulation (i.e., the number of ad opportunities evaluated in a segment) varies based on the modification of the ad conditions [0030] … The ad conditions indicate specific attributes of the ad campaign, which may be modified during the simulation of the set of ad queries, and between each segment of ad queries. The ad conditions that are modified may include a bidding value for an advertisement, such as a paced bid amount, bidding frequency, and targeting criteria [0033] … simulation module 225 may use the results of the simulation to determine the size of the next segment to simulate. Stated another way, the simulation module 225 determines the frequency of segmenting the set of ad queries and the total number of segments simulated by the simulation module 225. That is, the segmenting frequency indicates how frequently a new segment is generated. Between each segment, the ad pacing module 230 may revise the ad conditions. [0004] … evaluation of each segment results in a simulation of many ad queries without updating conditions of the ad selection. After each ad segment, the advertising system evaluates the ad results for the segment and modifies conditions for the advertising selection process affected by the ad results for use with the next ad segment. These conditions may include a bid frequency, paced bid amount, and targeting criteria for advertisements. The segmented ads permit the advertising system to simulate)
generating a simulation execution of the content delivery platform for the particular market using the set of simulation configurations; and recording outcomes of the simulation execution ([0004] … simulation of many ad queries without updating conditions of the ad selection. After each ad segment, the advertising system evaluates the ad results for the segment and modifies conditions for the advertising selection process affected by the ad results for use with the next ad segment. These conditions may include a bid frequency, paced bid amount, and targeting criteria for advertisements. The segmented ads permit the advertising system to simulate a large number of advertisements and maintain more accurate simulated results. [0006] … various metrics may be calculated for the simulated results for an advertiser, such as a number of impressions and reach of the advertising campaign, spending, ad effectiveness, and so forth. [0007] Using the simulation, the advertising system operator or an advertiser can perform A/B or other testing to evaluate the effects of changing various features of the advertising auction system, such as modifying a pacing algorithm, advertising auction (bidding) model, allocation of advertisers to ad queries, reserve price, and other changes to the ad selection process. [0029] … when an advertisement simulation is performed by the simulation module 225, the results of the simulated advertisement may also be stored in the ad result store 220. The ad results indicate, for each of the ad queries, which advertisement was selected for the advertisement slots in an ad query and what price is paid by the advertiser for the ad placement. Each simulation of ad selection may store results in ad results store 220).
As per claim 2, Sodomka teaches: wherein the particular market is defined at least in part by one or more of a geographic parameter, a user parameter, and/or a user device parameter ([0024] … Targeting criteria included in an advertisement request specify one or more characteristics of users eligible to be presented with content in the advertisement request. For example, targeting criteria are a filter to apply to fields of a user profile and/or actions associated with a user to identify users having user profile information or actions satisfying at least one of the targeting criteria. Hence, the targeting criteria allow an advertiser to identify groups of users matching specific targeting criteria, simplifying subsequent distribution of advertisements to groups of users).
As per claim 3, Sodomka teaches: wherein the historical data generated from the real-world execution of the content delivery platform includes historical bidding data, the historical bidding data including data that represents bidding logic used by each campaign that was active for the particular market, ([0027] The ad query store 210 includes a record of advertising queries received by the advertising system 100. The ad query store 210 thus records ad queries previously received and served by the advertising system 100. [0029] The ad result store 220 maintains a record of advertisements selected for a set of advertising queries. For example, the original selection of advertising results that were selected when ads were served by the advertising system 100 may be stored in the ad result store 220. [0031] … determine the competing advertisers for an ad query. In one embodiment, the competing advertisers are identified in the ad query store 210 as the advertisers that previously bid on the ad query when the ad query was originally provided an advertisement by advertising system 100.
the bidding data indicating at least one of a bidding strategy, a bidding pace methodology, and/or a bidding price constraint for a corresponding active campaign of the particular market ([0022] … The advertising campaign may specify a budget, duration, bid amount, bid frequency, targeting criteria, among other parameters. The bid amount is associated with an advertisement by an advertiser and is used to determine an expected value, such as monetary compensation, provided by an advertiser to the advertising system 100 if the advertisement is presented to a user, if the advertisement receives a user interaction, or based on any other suitable condition. For example, the bid amount specifies a monetary amount that the social networking system 100 receives from the advertiser if the advertisement is displayed and the expected value is determined by multiplying the bid amount by a probability of the advertisement being accessed. When a budget and duration are specified, as the advertisements are provided to client devices 110, the advertiser spends a portion of the budget to serve the advertisement. The duration indicates a length of time for the advertising campaign to spend the budget. That is, it is expected that the budget will be spent during the advertising campaign's duration. [0030] …The ad conditions that are modified may include a bidding value for an advertisement, such as a paced bid amount, bidding frequency, and targeting criteria.)
As per claim 4, Sodomka teaches: wherein the set of simulation configurations include a modification to a bidding logic used by one or more campaigns that were active in the particular market ([0003] … An advertiser or operator of the adverting system may wish to know the performance of advertisements under different conditions from the conditions under which ads were originally served [0004] … simulation of many ad queries without updating conditions of the ad selection. After each ad segment, the advertising system evaluates the ad results for the segment and modifies conditions for the advertising selection process affected by the ad results for use with the next ad segment. These conditions may include a bid frequency, paced bid amount, and targeting criteria for advertisements. The segmented ads permit the advertising system to simulate a large number of advertisements and maintain more accurate simulated results. [0007] …advertiser can perform A/B or other testing to evaluate the effects of changing various features of the advertising auction system, such as modifying a pacing algorithm, advertising auction (bidding) model [0030] …The ad conditions indicate specific attributes of the ad campaign, which may be modified during the simulation)
As per claim 5, Sodomka teaches: wherein the modification includes a change to at least one of a bidding strategy, a pacing strategy or a price input ([0004] … simulation of many ad queries without updating conditions of the ad selection. After each ad segment, the advertising system evaluates the ad results for the segment and modifies conditions for the advertising selection process affected by the ad results for use with the next ad segment. These conditions may include a bid frequency, paced bid amount, and targeting criteria for advertisements. The segmented ads permit the advertising system to simulate a large number of advertisements and maintain more accurate simulated results. [0007] Using the simulation, the advertising system operator or an advertiser can perform A/B or other testing to evaluate the effects of changing various features of the advertising auction system [0022] … The advertising campaign may specify a budget, duration, bid amount, bid frequency, targeting criteria, among other parameters. The bid amount is associated with an advertisement by an advertiser and is used to determine an expected value, such as monetary compensation, provided by an advertiser to the advertising system 100 if the advertisement is presented to a user, if the advertisement receives a user interaction, or based on any other suitable condition. For example, the bid amount specifies a monetary amount that the social networking system 100 receives from the advertiser if the advertisement is displayed and the expected value is determined by multiplying the bid amount by a probability of the advertisement being accessed. When a budget and duration are specified, as the advertisements are provided to client devices 110, the advertiser spends a portion of the budget to serve the advertisement. The duration indicates a length of time for the advertising campaign to spend the budget. That is, it is expected that the budget will be spent during the advertising campaign's duration [0034] To perform this comparison, the simulation module 225 stores the ad conditions for previously simulated segments and compares the ad conditions for previous segments to the conditions calculated for the next segment by the ad pacing module 230 to determine a change in ad conditions. The simulation module 225 may maintain a threshold for individual types of conditions (e.g., pacing, targeting criteria, or bid frequency), or the change in each condition may be combined and compared to a threshold.).
As per claim 6, Sodomka teaches: wherein the historical data includes historical auction data, the historical auction data comprising representing data that identifies a plurality of auction processes that took place to identify a content item for each available slot of the plurality of slots, ([0027] The ad query store 210 includes a record of advertising queries received by the advertising system 100. The ad query store 210 thus records ad queries previously received and served by the advertising system 100…the advertisements that were previously selected for the advertisement query…may represent one or more advertisement slots to be provided to the client device 110. For example, a given ad query may indicate that three advertisement slots are available [0029] The ad result store 220 maintains a record of advertisements selected for a set of advertising queries. …the original selection of advertising results that were selected when ads were served by the advertising system 100 may be stored… which advertisement was selected for the advertisement slots in an ad query and what price is paid by the advertiser for the ad placement. [0030] The simulation module 225 performs simulation of a set of ad queries to assign advertisers to ad queries. To perform the simulation, the simulation module 225 identifies ad results for a portion of the ad queries termed a segment. [0039] The actual spending 310 of a campaign is based on the ad queries for which the campaign is selected as the winning bid and the price for the ad placement.)
the auction data identifying, for each auction process, (i) one or more candidate campaigns that submitted one or more bids for the auction process, and ([0031] … the competing advertisers are identified in the ad query store 210 as the advertisers that previously bid on the ad query when the ad query was originally provided an advertisement by advertising system 100. [0043] … thirty advertisers 510, 1-30, provide bids to place advertisements with each of the ad queries 500)
(ii) an outcome of the auction process. ([0029] The ad result store 220 maintains a record of advertisements selected for a set of advertising queries. For example, the original selection of advertising results that were selected when ads were served by the advertising system 100 may be stored in the ad result store 220 … The ad results indicate, for each of the ad queries, which advertisement was selected for the advertisement slots in an ad query and what price is paid by the advertiser for the ad placement. [0044] … ad results 530A specifying the advertiser and related price winning the auction for each ad query.).
As per claim 7, Sodomka teaches: wherein the modification includes a change to one or more auction processes that took place for the particular market ([0007] … changing various features of the advertising auction system, such as modifying a pacing algorithm, advertising auction (bidding) model, allocation of advertisers to ad queries, reserve price, and other changes to the ad selection process [0032] … the final price paid by the winning advertiser in the bidding process may be a first-price auction or a second-price (Vickrey) auction.)
As per claim 8, Sodomka teaches: wherein the set of simulation configurations include a modification to an auction process used to select which content item to place in one or more of the available slots ([0007] … perform A/B or other testing to evaluate the effects of changing various features of the advertising auction system… modifying a pacing algorithm, advertising auction (bidding) model, allocation of advertisers to ad queries, reserve price, and other changes to the ad selection process. [0032] The ad model used for the advertising auction may also vary … The ad model may apply a “price-per-impression” model, a “price-per-click” model, or price-per-conversion … Certain ad queries may also present more than one ad slot for which an advertiser may be selected. These ad slots may also be treated as having a uniform price, or each advertising slot may be discounted relative to the most valuable slot. Thus, the advertising slots may have descending value based on the location on a page being viewed by the user.).
As per claim 9, Sodomka teaches: wherein the modification to the auction process includes a modification to how the auction process scores and/or ranks individual bids ([0007] … perform A/B or other testing to evaluate the effects of changing various features of the advertising auction system, such as modifying a pacing algorithm, advertising auction (bidding) model, allocation of advertisers to ad queries, reserve price, and other changes to the ad selection process [0030] … The ad model is a formula or other algorithm for determining the advertiser and price for a given ad query using the ad conditions. The ad model is typically an auction that determines a winning bid amount and advertiser from among competing advertisers. [0032] … The ad model may apply a “price-per-impression” model, a “price-per-click” model, or price-per-conversion. To determine the auction winner in price-per-click and price-per-conversion models, the ad model converts a bid price to an expected value that accounts for the likelihood that a user clicks or performs the conversion activity).
As per claim 10, Sodomka teaches: wherein the historical data further comprises historical slot data that identifies a plurality of available slots that existed in the particular market, each available slot of the plurality of available slots being generated as a result of a content placement event on a corresponding user device of the plurality of user device ([0016] … advertising system 100 to fill advertising slots on a page of the ad publisher [0027] The ad query store 210 includes a record of advertising queries received by the advertising system 100. The ad query store 210 thus records ad queries previously received and served by the advertising system 100 … Each ad query represents a request from a client device for an advertisement and is associated with a user of the client device. The ad query may indicate, for example, that a request was received from a specific user at a specific time and may represent one or more advertisement slots to be provided to the client device 110. For example, a given ad query may indicate that three advertisement slots are available [0029] The ad result store 220 maintains a record of advertisements selected for a set of advertising queries. For example, the original selection of advertising results that were selected when ads were served by the advertising system 100 may be stored in the ad result store 220 … The ad results indicate, for each of the ad queries, which advertisement was selected for the advertisement slots in an ad query and what price is paid by the advertiser for the ad placement.).
As per claim 11, Sodomka teaches: generating a set of synthetic available slots; and generating the simulation execution includes utilizing the synthetic available slots and the historical slot data ([0007] … advertiser can perform A/B or other testing to evaluate the effects of changing various features; tests/simulates changes to features (slots). A simulated slot is ‘synthetic’. [0015] … the advertising system 100 simulates advertisement selection for a set of historical ad queries, permitting effective analysis of actual advertising requests at a large scale. [0027] … a request was received from a specific user at a specific time and may represent one or more advertisement slots to be provided to the client device 110. For example, a given ad query may indicate that three advertisement slots are available for the user.)
As per claim 12, Sodomka teaches: determining, from the recorded outcomes, a performance or efficacy of the simulation execution. ([0004] … the advertising system evaluates the ad results for the segment and modifies conditions for the advertising selection process affected by the ad results [0006] … After evaluation, various metrics may be calculated for the simulated results for an advertiser, such as a number of impressions and reach of the advertising campaign, spending, ad effectiveness, and so forth. [0029] … selection of advertising results that were selected when ads were served by the advertising system 100 may be stored in the ad result store 220…The ad results indicate, for each of the ad queries, which advertisement was selected for the advertisement slots in an ad query and what price is paid [0036] … results from a simulated advertisement. The ad report module 235 may generate reports describing the simulated results, such as the reach and number of advertisements provided by an advertiser in the simulation).
As per claim 13, Sodomka teaches: 13. The computer system of claim 12, wherein determining the performance or efficacy of the simulation execution includes determining a quantity and/or type of user interaction with placement of one or more content items in the simulation execution. ([0006] … After evaluation, various metrics may be calculated for the simulated results for an advertiser, such as a number of impressions and reach of the advertising campaign… [0029] …when an advertisement simulation is performed by the simulation module 225, the results of the simulated advertisement may also be stored in the ad result store 220. The ad results indicate, for each of the ad queries, which advertisement was selected for the advertisement slots in an ad query and what price is paid by the advertiser for the ad placement. Each simulation of ad selection may store results in ad results store 220 [0032] …The ad model may apply a “price-per-impression” model, a “price-per-click” model, or price-per-conversion. To determine the auction winner in price-per-click and price-per-conversion models, the ad model converts a bid price to an expected value that accounts for the likelihood that a user clicks or performs the conversion activity. [0036] The ad report module 235 analyzes the ad results from a simulated advertisement. The ad report module 235 may generate reports describing the simulated results, such as the reach and number of advertisements provided by an advertiser in the simulation and cost to the advertiser of the advertisement placement selected in the simulation.)
As per claim 16, this claim recites limitations substantially similar to those addressed by the rejection of claim 1, above; therefore, the same rejection applies.
As per claim 17, this claim recites limitations substantially similar to those addressed by the rejection of claim 2, above; therefore, the same rejection applies.
As per claim 18, this claim recites limitations substantially similar to those addressed by the rejection of claim 3, above; therefore, the same rejection applies.
As per claim 19, this claim recites limitations substantially similar to those addressed by the rejection of claim 4, above; therefore, the same rejection applies.
As per claim 20, this claim recites limitations substantially similar to those addressed by the rejection of claim 1, above; therefore, the same rejection applies.
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.
Claim(s) 14 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2016/0283974 (Sodomka); in view of US 2013/0339126 (Cui).
As per claim 14, although not explicitly taught by Sodomka, Cui teaches: comparing a performance or efficacy of the real-world execution with the performance or efficacy of the simulation execution ([0042] … The estimated data 204 may include a predicted number of impressions, clicks, and/or conversions. … In an alternative embodiment, the estimated data 204 may be input into an aggregator for comparing with campaign history data 208 from the advertisement database 126. In particular, the aggregator 206 may compare and refine the predictions (estimated data 204) by comparing with actual historical data (e.g. a click history of a similar ad). [0056] … the historical impressions, clicks and conversions for the campaigns to be forecasted may be used as calibration for final forecasting results…. simulation based forecasting results may be adapted to generate the performance changes (measured by ratio) caused by the changes in campaign parameters in the query against the campaign parameters employed in the campaign history to adjust the baseline).
It would have been obvious, before the effective filing date of the claimed invention, for one of ordinary skill in the art to have modified the teachings of Sodomka with the aforementioned teachings of Cui with the motivation of making performance changes (Cui [0056]). Further, one of ordinary skill in the art would have recognized that applying the teachings of Cui to the system of Sodomka would have yielded predictable results and doing so would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for evaluation of simulation results.
As per claim 15, although not explicitly taught by Sodomka, Cui teaches: wherein comparing the metric or attribute of the real-world execution with a corresponding metric or attribute of the simulation execution includes comparing a performance metric for placement of one or more content items in the real-world execution with the performance metric determined for the simulation execution ([0042] … The estimated data 204 may include a predicted number of impressions, clicks, and/or conversions. … In an alternative embodiment, the estimated data 204 may be input into an aggregator for comparing with campaign history data 208 from the advertisement database 126. In particular, the aggregator 206 may compare and refine the predictions (estimated data 204) by comparing with actual historical data (e.g. a click history of a similar ad). [0056] … the historical impressions, clicks and conversions for the campaigns to be forecasted may be used as calibration for final forecasting results…. simulation based forecasting results may be adapted to generate the performance changes (measured by ratio) caused by the changes in campaign parameters in the query against the campaign parameters employed in the campaign history to adjust the baseline).
It would have been obvious, before the effective filing date of the claimed invention, for one of ordinary skill in the art to have modified the teachings of Sodomka with the aforementioned teachings of Cui with the motivation of making performance changes (Cui [0056]). Further, one of ordinary skill in the art would have recognized that applying the teachings of Cui to the system of Sodomka would have yielded predictable results and doing so would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for evaluation of simulation results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2013/0117070 – discloses a system that simulates a bidding process.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALAN TORRICO-LOPEZ whose telephone number is (571)272-3247. The examiner can normally be reached M-F 10AM-5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Beth Boswell can be reached at (571)272-6737. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ALAN TORRICO-LOPEZ/ Primary Examiner, Art Unit 3625
Prosecution Insights