DETAILED ACTION
Claims 1-20 are pending. Claims 1-20 are considered in this Office 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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/9/2025 has been acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. The initialed and dated copy of Applicant’s IDS form 1449 is attached to the instant Office action.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1, 9, and 17 of the current application (Hereby known as ‘681) are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11,593,819 (Hereby known as ‘819). Although the claims at issue are not identical, they are not patentably distinct from each other because:
Regarding Claims 1, 9, and 17, Claims 1, 9, and 17 of the current application (‘681) recite substantially similar steps of '681 - Claim 1.
Claims 1, 9, and 17 of ‘681 recite the steps of:
displaying one or more content items to a first user;
measuring a first number of interactions performed by the first user after the one or more content items are displayed to the first user;
measuring a second number of interactions performed by a second user when none of the one or more content items are displayed to the second user;
determining a measured difference between the first number of interactions and the second number of interactions;
accessing a user interaction model that comprises a plurality of layers of a neural network, wherein the user interaction model is trained by:
applying the user interaction model to generate a predicted difference, the predicted difference indicating a difference between a first predicted number of interactions performed by the first user after the one or more content items are displayed to the first user and a second predicted number of the interaction performed by the second user when none of the one or more content items are displayed to the second user, and
backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction model, the backpropagating performed through the neural network and one or more of the error terms based on the measured difference and the predicted difference;
identifying an opportunity to display content items to an additional user;
applying the user interaction model to determine a predicted value of the additional user when a particular content item is displayed to the additional user;
determining, using the predicted value, whether to display the particular content item to the additional user; and
causing, based on determining to display the particular content item to the additional user, the particular content item to be displayed to the additional user.
Whereas Claim 1 of ‘819 states:
obtaining training data that comprises identifiers of a plurality of users of an online concierge system, with a label applied to each identifier of a user, the label applied to an identifier of a user comprising a value representing a difference between a number of an interaction performed by the user after one or more content items are displayed to the user and a number of the interaction performed by the user when none of the one or more content items are displayed to the user;
initializing a user interaction network that comprises a plurality of layers of a neural network;
for each of a plurality of the examples of the training data:
applying the user interaction network to the identifier of the user to generating a predicted value of a user corresponding to the identifier of the user, the predicted value indicating a difference between a predicted number of the interaction performed by the user after one or more content items are displayed to the user by the online concierge system and a predicted number of the interaction performed by the user when none of the one or more content items are displayed to the user, and
backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction network, the backpropagating performed through the neural network and one or more of the error terms based on a difference between a label applied to the user identifier and the generated predicted value of the user; and
storing the set of parameters of the layers of the user interaction network on the computer readable storage medium as parameters of the user interaction model, wherein the user interaction model is configured to receive an identifier of an additional user and to generate a predicted value of the additional user when a content item is displayed to the additional user by the online concierge system.
These are obvious variants of each other as both recite substantially the same limitations. Further, elimination of an element or its functions is deemed to be obvious in light of prior art teachings of at least the recited element or its functions (see In re Karlson, 136 USPQ 184, 186; 311 F2d 581 (CCPA 1963)), thereby rendering the elimination of any elements recited in the claims of the related patent (that are not recited in the instant claims) obvious.
Thus, Claims 1, 9, and 17 of the current application are obvious variants of claim 1 in ‘819.
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 an abstract idea without significantly more.
Claims 1, 9, and 17 recite limitations for displaying one or more content items to a first user (Transmitting Information, a judgment, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), measuring a first number of interactions performed by the first user after the one or more content items are displayed to the first user (Collecting and Analyzing the Information, an observation and evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), measuring a second number of interactions performed by a second user when none of the one or more content items are displayed to the second user (Collecting and Analyzing the Information, an observation and evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), determining a measured difference between the first number of interactions and the second number of interactions (Analyzing the Information, an evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), accessing a user interaction model that comprises a plurality of layers of a neural network, wherein the user interaction model is trained by: applying the user interaction model to generate a predicted difference, the predicted difference indicating a difference between a first predicted number of interactions performed by the first user after the one or more content items are displayed to the first user and a second predicted number of the interaction performed by the second user when none of the one or more content items are displayed to the second user, and backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction model, the backpropagating performed through the neural network and one or more of the error terms based on the measured difference and the predicted difference; identifying an opportunity to display content items to an additional user (Collecting and Analyzing the Information, an observation and evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), applying the user interaction model to determine a predicted value of the additional user when a particular content item is displayed to the additional user (Analyzing the Information, an evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), determining, using the predicted value, whether to display the particular content item to the additional user (Analyzing the Information, an evaluation, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), and causing, based on determining to display the particular content item to the additional user, the particular content item to be displayed to the additional user (Transmitting the Information, a judgment, a Mental Process; a Fundamental Economic Practice, i.e. data analytics for predicting user value; a Certain Method of Organizing Human Activity), which under their broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a computer system, processor, computer-readable medium, and memory, nothing in the claim element precludes the step from practically being performed or read into the mind for the purposes of presenting content. For example, but for the use of computer system, processor, etc. language, determining a measured difference between the first number of interactions and second number of interactions encompasses a manager, supervisor, data analyst, anyone really, watch someone interacting with a computer and recording it, and then noting a difference between types of interactions, an observation, evaluation, and judgment. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Further, as described above, these processes recite limitations for a Fundamental Economic Process, a “Method of Organizing Human Activity”. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the above stated additional elements to perform the abstract limitations as above. The system, processor, memory, and medium are recited at a high-level of generality (i.e., as a generic processor/module performing a generic computer function of storing, retrieving, sending, and processing data) such that they amounts no more than mere instructions to apply the exception using generic computer components. Even if taken as an additional element, the receiving and transmission steps above would be insignificant extra-solution activity as these are receiving, storing, and transmitting data as per the MPEP 2106.05(d). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they 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, when considered both individually and as an ordered combination. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements being used to perform the abstract limitations stated above amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible. Applicant’s specification states:
“[0078] Embodiments of the invention may also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, and/or it may comprise a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a tangible computer readable storage medium, which include any type of tangible media suitable for storing electronic instructions and coupled to a computer system bus. Furthermore, any computing systems referred to in the specification may include a single processor or may be architectures employing multiple processor designs for increased computing capability. “
Which shows any general-purpose computing device can be used, as per the specification above, and from this interpretation, one would reasonably deduce the aforementioned steps are all functions that can be done on generic components, such as a laptop, desktop, tablet, etc., and thus application of an abstract idea on a generic computer, as per the Alice decision and not similar to Berkheimer, but for edification the Applicant’s specification has been used as above satisfying any such requirement. For the collecting and transmission steps that were considered extra-solution activity in Step 2A above, if they were to be considered an additional element, they have been re-evaluated in Step 2B and determined to be well-understood, routine, conventional, activity in the field. The background does not provide any indication that the additional elements, such as the system, memory, processor, etc., nor the receiving and transmitting steps as above, are anything other than a generic, and the MPEP Section 2106.05(d) indicates that mere collection or receipt, storing, or transmission of data is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept. The claim is not patent eligible.
Claims 2-8, 10-16, and 18-20 contain the identified abstract ideas, further narrowing them, with no new additional elements to be considered under prong 2 as part of the Alice analysis of the MPEP for a practical or under 2B, and thus not significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. Therefore, the claims and dependent claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
Allowable Subject Matter
Claims 1-20 have overcome the prior art and would be allowable if amended to overcome the 35 USC 101 rejections.
The closest prior art of record is Helenius (U.S. Publication No. 2020/031,1585), Bhatia (U.S. Publication No. 2020/010,4697), and George (U.S. Publication No. 2019/033,5006). Helenius, a system and method for multi-model based account/product sequence recommendations, teaches obtaining training data that comprises identifiers of a plurality of users, a label used as well as an identifier of a user, initializing a user interaction network that comprises a plurality of layers of a neural network, and for each of a plurality of the examples of the training data, using machine learning, but it does not explicitly state it is configured to the label applied to an identifier of a user comprising a value representing a difference between a number of an interaction performed by the user after one or more content items are displayed to the user and a number of the interaction performed by the user when none of the one or more content items are displayed to the use, nor does it teach the backpropagation being performed in the manner claimed below. Bhatia, a system and method for generating homogenous user embedding representations from heterogenous user interaction data using a neural network, teaches the label applied to an identifier of a user comprising a value representing a difference between a number of an interaction performed by the user after one or more content items are displayed to the user and a number of the interaction performed by the user when none of the one or more content items are displayed to the user, but does not teach the backpropagating in relation to a generated predicted value of a user corresponding to the user, nor does it teach the updating of the parameters used with the backpropagation and the neural network. George, a method and system for dynamic customization of structure, teaches storing the set of parameters, layers, a computer readable storage medium, the user interaction model is configured to receive an identifier of an additional user, to generate a predicted value of a user and additional user additional user, but not when a content item is displayed to the additional user by the online concierge system, nor does it teach specifically applying the user interaction network to the identifier of the user to generating a predicted value of a user corresponding to the identifier of the user, the predicted value indicating a difference between a predicted number of the interaction performed by the user after one or more content items are displayed to the user by the online concierge system and a predicted number of the interaction performed by the user when none of the one or more content items are displayed to the user, and backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction network, the backpropagating performed through the neural network and one or more of the error terms based on a difference between a label applied to the user identifier and the generated predicted value of the user. None of the above prior art explicitly teaches applying the user interaction network to the identifier of the user to generating a predicted value of a user corresponding to the identifier of the user, the predicted value indicating a difference between a predicted number of the interaction performed by the user after one or more content items are displayed to the user by the online concierge system and a predicted number of the interaction performed by the user when none of the one or more content items are displayed to the user, and backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction network, the backpropagating performed through the neural network and one or more of the error terms based on a difference between a label applied to the user identifier and the generated predicted value of the user, and these are the reasons which adequately reflect the Examiner's opinion as to why Claims 1-20 are allowable over the prior art of record.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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/JOSEPH M WAESCO/Primary Examiner, Art Unit 3625B 2/28/2026