DETAILED ACTION
Status of the Claims
The following is a Final Office Action in response to amendments and arguments filed 20 February 2026.
Claims 1 and 11 have been amended.
Claims 1, 3-4, 8-9, 11, 13-14, 18-19, and 21-26 are pending and have been examined.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 20 February 2026 have been fully considered and are not persuasive for a plurality of reasons. Firstly, Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Secondly, Applicant's arguments do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which he or she thinks the claims present in view of the state of the art disclosed by the references cited or the objections made. Further, they do not show how the amendments avoid such references or objections. Thirdly, and contrary to Applicant’s assertions, Mazed does in fact teach the amended aspects of the claims. As previously cited in the last several office actions, Mazed is able to “Furthermore, in step 4052, the unified algorithm 320 (in particular the predictive algorithm 380) in the social wallet 100 can initially determine a set of relevant users for a targeted advertisement for a specified product and/or service. In step 4053, the unified algorithm 320 in the social wallet 100 can send a coupon(s) (e.g., in the form of a text/e-mail link/picture mail/video mail) related to the specified product and/or service from the merchants 180s to the profiles of the above set of relevant users 160s. In step 4054, the above set of relevant users can share the coupon(s) (e.g., in the form of a text/e-mail link/picture mail/video mail) related to the specified product and/or service from the merchants 180s with the other users 160s' mobile internet devices 300s, in real time (preferably via the other users 160s' profiles in the social wallet 100). If a targeted advertisement campaign does not receive a response greater than at a pre-determined % (e.g., 10%), then in step 4055, the unified algorithm 320 (in particular the predictive algorithm 380, the intelligence rendering algorithm 400 and the self-learning (including relearning) algorithm 420) in the social wallet 100 can iterate (fine-tune) to find another set of relevant users for the targeted advertisement, until the targeted advertisement would be concluded successful to stop, when the targeted advertisement campaign receives the response greater than at the pre-determined % (e.g., 10%) (Mazed ¶94-¶97).” This is clearly the “...in which the customer information includes aggregated personal profiles generated by the computing system for the customers different from the first customer and is indicative of interactions of the customers with one or more entities and outcomes of interactions, the second predictor generated by applying machine learning to the database of the customer information of customers different from the first customer...” as Mazed is able to iteratively select (via machine learning) relevant users (i.e. the users with the profiles deemed relevant by some threshold percentage). As such, this argument is not persuasive, and the rejection not withdrawn.
In response to arguments in reference to any depending claims that have not been individually addressed, all rejections made towards these dependent claims are maintained due to a lack of reply by the Applicants in regards to distinctly and specifically pointing out the supposed errors in the Examiner's prior office action (37 CFR 1.111). The Examiner asserts that the Applicants only argue that the dependent claims should be allowable because the independent claims are unobvious and patentable over the prior art.
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 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.
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.
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claim 1, 3-4, 8-9, 11, 13-14, 18-19, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ow et al. (US PG Pub. 2019/0324958) and Schur (US PG Pub. 2019/0205148) further in view of Mazed (US PG Pub. 2017/0221032).
As per claims 1 and 11, Ow discloses a computer-implemented method and system for personalizing protection of personal data pursuant to behavioral factors unique to an individual customer (hereafter "first customer"), the behavioral factors being learned from transaction data describing respective transactions occurring between the first customer and entities via a communication device of the first customer, the system comprising: a hardware processor; and a machine-readable storage medium on which is stored instructions that cause the hardware processor to execute a process, wherein the process comprises the steps of: the method comprising (processors, storage devices, Ow ¶203; distributed database, ¶293; system, ¶303):
storing, in a secured data vault, a customer profile of the first customer that comprises: personal data of the first customer; and the transaction data from each of the transactions (The AXEL blockchain will also provide a user-focused artificial intelligence (AI) component that will collect and parse transactional data on behalf of the user to give them instant access to information that was transacted utilizing the AXEL blockchain. Transactional information such as automobile maintenance schedules, medical history records, prescription drug records, and other lifestyle events can be processed and tracked through the AI functions of the AXEL blockchain. In one preferred embodiment, the AXEL blockchain AI component will collect and parse information pertaining to the history of a specific user to enable the user to instantly access information including but not limited to medical records, prescription medication history, car maintenance history, general sale and purchase history and other lifestyle metrics that can be managed and tracked through the private ledger and parsed with the artificial intelligence module. The information will be provided to the user based on a query submitted by the user pertaining to their transactional history within the AXEL blockchain. The purpose of the AI and the data parsing is to further enable the users of the AXEL blockchain to accurately track transactional history and provide feedback and historical information directly to the users of the AXEL blockchain. The AXEL blockchain AI component will act as a personal assistant or personal transaction manager for the user to enable them to easily recall historical information pertaining to transactions within the AXEL blockchain. In a preferred embodiment, the AI component is not intended or designated for use by any company or other entity seeking to collect user information for marketing or other purposes. The information may be stored and parsed at a local level to ensure the security and privacy of the AI functionality, Ow ¶36-¶38; belong to a distributed database, ¶293) (Examiner interprets the blockchain storage of the customer profile as the equivalent to the secured data vault);
providing a personal assistant application (hereafter "personal assistant") accessible to the first customer via the communication device, wherein the personal assistant is configured to access the personal data of the first customer in the customer profile pursuant to engagement rules that must be adhered to in order for the personal assistant to conduct the transactions with the entities on behalf of the first customer (The AXEL blockchain AI component will act as a personal assistant or personal transaction manager for the user to enable them to easily recall historical information pertaining to transactions within the AXEL blockchain, Ow ¶38; Security 840 function will verify (utilizing the process above) both the user/owner of the storage device as well as any user(s) registered within the AXEL blockchain who is given permission to access the storage. The verification for the user(s) accessing the storage will include a check of permissions as set by the user/owner of the storage and hosted within the AXEL database 815 function. As stated previously, these permissions will be set at the time the distributed storage capability is offered publicly for use by the user/owner of the storage device, ¶245; It is important to note (with respect to FIG. 9) that the user 905 can configure the wallet admin 935 and the financial admin 940 to facilitate any request automatically and without need for intervention by the user 905. The functional criteria for the wallet 935 and the financial 940 administrations can be preconfigured by the user 905 to set limits (both min and max) of transactions and balance inquires that do not require human intervention. This capability is intended to allow the user experience to be uninterrupted by authorization requests for the transfer of funds and cryptocurrencies to facilitate their transaction requirements, ¶263);
updating the customer profile pursuant to newly occurring ones of the transactions (hereafter "new transactions"), the new transactions including a first new transaction occurring between the first customer and a first one of the entities (hereafter "first entity") (the user private chain will be updated as each transaction is executed and subsequently verified within the system utilizing a consensus algorithm, Ow ¶39);
generating a first predictor from the updated customer profile, the first predictor comprising knowledge about the first customer derived, at least in part, from the data stored within the updated customer profile, the knowledge comprising a first one of the behavioral factors (hereafter "first behavioral factor") attributable to the first customer given a first characteristic related to the first new transaction (to enable the artificial intelligence mechanism (described in detail later in this submission) within the AXEL blockchain to parse the transactional data on behalf of the user and provide guidance and recommendations as to how the user can get more benefit from their participation within the AXEL blockchain, Ow ¶34; see other recommendations, ¶100 and ¶111);
augmenting the customer profile by storing therein the first predictor, wherein the first predictor: modifies at least one of the rules of the engagement rules and links the first behavioral factor to the first characteristic of the first transaction (parse the transactional data on behalf of the user for recommendations, Ow ¶34, ¶100 and ¶111; Transactional information such as automobile maintenance schedules, medical history records, prescription drug records, and other lifestyle events can be processed and tracked through the AI functions of the AXEL blockchain, ¶36; user executes a transaction, ¶249);
detecting the first characteristic as being present in an incoming one of the transactions (hereafter "incoming transaction") involving a second one of the entities (hereafter "second entity"), wherein the incoming transaction is instigated by the second entity and wherein the incoming transaction relates to a probable need of the first customer identified by the personal assistant from a condition derived from data stored in the updated customer profile (initiate transfer, issues receipt, Ow ¶10; user executes a transaction, Ow ¶249; to enable the artificial intelligence mechanism (described in detail later in this submission) within the AXEL blockchain to parse the transactional data on behalf of the user and provide guidance and recommendations as to how the user can get more benefit from their participation within the AXEL blockchain, ¶34; enable AXEL to provide recommendations for future transactions, ¶111; a user may execute a transaction within the AXEL blockchain without having any AXEL tokens (the native token for the AXEL blockchain) in their wallet. The AXEL wallet will automatically connect with the financial institution the user has pre-selected to manage the token exchange and perform this function. The external financial institution will remove currency (USD or other) from the user's pre-determined payment method (a bank account number, checking/savings account number, a debit or credit card, or other acceptable payment method) and exchange the currency for tokens to be used on the AXEL blockchain. The transaction requested by the user will then be executed through the wallet with the AXEL blockchain to pay for the subject transaction, ¶249; see also ¶54-¶55);
in response to detecting the first characteristic and without requiring input from the first customer, automatically modifying, in accordance with the first behavioral factor of the first predictor, a manner in which the personal assistant conducts the incoming transaction with the second entity on behalf of the first customer (a user may execute a transaction within the AXEL blockchain without having any AXEL tokens (the native token for the AXEL blockchain) in their wallet. The AXEL wallet will automatically connect with the financial institution the user has pre-selected to manage the token exchange and perform this function. The external financial institution will remove currency (USD or other) from the user's pre-determined payment method (a bank account number, checking/savings account number, a debit or credit card, or other acceptable payment method) and exchange the currency for tokens to be used on the AXEL blockchain. The transaction requested by the user will then be executed through the wallet with the AXEL blockchain to pay for the subject transaction, Ow ¶249; It is important to note (with respect to FIG. 9) that the user 905 can configure the wallet admin 935 and the financial admin 940 to facilitate any request automatically and without need for intervention by the user 905. The functional criteria for the wallet 935 and the financial 940 administrations can be preconfigured by the user 905 to set limits (both min and max) of transactions and balance inquires that do not require human intervention. This capability is intended to allow the user experience to be uninterrupted by authorization requests for the transfer of funds and cryptocurrencies to facilitate their transaction requirements, ¶263; see also ¶54-¶55); wherein:
the modified at least one of the rules of the engagement rules comprises a maximum price payable by the personal assistant in relation to the incoming transaction of the probable need without obtaining the first customer's permission and designates a preferred brand in relation to a product domain of the probable need (governs the preset minimums and maximums that the user 905 has provisioned for their wallet administration 935 to govern financial transactions, Ow ¶257; It is important to note (with respect to FIG. 9) that the user 905 can configure the wallet admin 935 and the financial admin 940 to facilitate any request automatically and without need for intervention by the user 905. The functional criteria for the wallet 935 and the financial 940 administrations can be preconfigured by the user 905 to set limits (both min and max) of transactions and balance inquires that do not require human intervention. This capability is intended to allow the user experience to be uninterrupted by authorization requests for the transfer of funds and cryptocurrencies to facilitate their transaction requirements, ¶263; user transaction history, for recommendations ¶36-¶37) (Examiner notes the provisioned wallet that governs the minimum and maximums for transactions as the ability to have a maximum price payable by the personal assistant. Examiner also notes the use of transaction histories to make future recommendations as the ability to identify preferred brand/domains); and
the personal assistant conducts each of the transactions via selectively sharing aspects of the personal data of the first customer with the entities so to maximize an anonymity of the first customer relative to the entities by limiting a disclosure of personally identifiable information of the first customer stored in the customer profile (This vault (similar to a digital wallet) will be controlled by keys that the user/owner of the identification can share at their discretion to enable others to positively identify the user/owner for the purpose of transactions requiring such identification. The vault will exist on the user/owner controlled device(s) and may be backed-up to ensure integrity of the identity. As third-parties are allowed to verify the identity of the user/owner, these verification authorizations and confirmations will also be stored in the user identity vault to further add to the validity and authenticity of the user/owner identity , Ow ¶51; In a preferred embodiment, the witness mirror blocks created on the witness private chain during a witness event contain encrypted information which prevents the user of the witness node from seeing any private or personal details from the subject transaction. Details such as party names, items being bought or sold, the pricing of the subject items, vendor names, and other private details of the transaction are encrypted to protect the privacy of the parties that participated in the subject transaction. However, in order for the witness function to perform properly, this information is shared (in an encrypted format) with each witness performing the consensus algorithm via the witness function. Once the witness event is complete (regardless of whether the transaction was authorized or declined) the blocks added to the witness ledger will be encrypted to protect the privacy of the participants of the subject transaction, Ow ¶42)
the automatically modifying the manner in which the personal assistant conducts the incoming transaction comprises (governs the preset minimums and maximums that the user 905 has provisioned for their wallet administration 935 to govern financial transactions, Ow ¶257; It is important to note (with respect to FIG. 9) that the user 905 can configure the wallet admin 935 and the financial admin 940 to facilitate any request automatically and without need for intervention by the user 905. The functional criteria for the wallet 935 and the financial 940 administrations can be preconfigured by the user 905 to set limits (both min and max) of transactions and balance inquires that do not require human intervention. This capability is intended to allow the user experience to be uninterrupted by authorization requests for the transfer of funds and cryptocurrencies to facilitate their transaction requirements, ¶263);
completing a purchase for the first customer of a product within the product domain from the designated preferred brand as identified by the modified at least one of the engagement rules; per the modified maximum price (governs the preset minimums and maximums that the user 905 has provisioned for their wallet administration 935 to govern financial transactions, Ow ¶257; It is important to note (with respect to FIG. 9) that the user 905 can configure the wallet admin 935 and the financial admin 940 to facilitate any request automatically and without need for intervention by the user 905. The functional criteria for the wallet 935 and the financial 940 administrations can be preconfigured by the user 905 to set limits (both min and max) of transactions and balance inquires that do not require human intervention. This capability is intended to allow the user experience to be uninterrupted by authorization requests for the transfer of funds and cryptocurrencies to facilitate their transaction requirements, ¶263);
per rules included within the trusted relationship log related to sharing personal data of the first customer associated with the second entity (This vault (similar to a digital wallet) will be controlled by keys that the user/owner of the identification can share at their discretion to enable others to positively identify the user/owner for the purpose of transactions requiring such identification. The vault will exist on the user/owner controlled device(s) and may be backed-up to ensure integrity of the identity. As third-parties are allowed to verify the identity of the user/owner, these verification authorizations and confirmations will also be stored in the user identity vault to further add to the validity and authenticity of the user/owner identity , Ow ¶51; In a preferred embodiment, the witness mirror blocks created on the witness private chain during a witness event contain encrypted information which prevents the user of the witness node from seeing any private or personal details from the subject transaction. Details such as party names, items being bought or sold, the pricing of the subject items, vendor names, and other private details of the transaction are encrypted to protect the privacy of the parties that participated in the subject transaction. However, in order for the witness function to perform properly, this information is shared (in an encrypted format) with each witness performing the consensus algorithm via the witness function. Once the witness event is complete (regardless of whether the transaction was authorized or declined) the blocks added to the witness ledger will be encrypted to protect the privacy of the participants of the subject transaction, Ow ¶42); and
rules limiting disclosure of personally identifiable information of the first customer so that the anonymity of the first customer is maximized (This vault (similar to a digital wallet) will be controlled by keys that the user/owner of the identification can share at their discretion to enable others to positively identify the user/owner for the purpose of transactions requiring such identification. The vault will exist on the user/owner controlled device(s) and may be backed-up to ensure integrity of the identity. As third-parties are allowed to verify the identity of the user/owner, these verification authorizations and confirmations will also be stored in the user identity vault to further add to the validity and authenticity of the user/owner identity , Ow ¶51; In a preferred embodiment, the witness mirror blocks created on the witness private chain during a witness event contain encrypted information which prevents the user of the witness node from seeing any private or personal details from the subject transaction. Details such as party names, items being bought or sold, the pricing of the subject items, vendor names, and other private details of the transaction are encrypted to protect the privacy of the parties that participated in the subject transaction. However, in order for the witness function to perform properly, this information is shared (in an encrypted format) with each witness performing the consensus algorithm via the witness function. Once the witness event is complete (regardless of whether the transaction was authorized or declined) the blocks added to the witness ledger will be encrypted to protect the privacy of the participants of the subject transaction, Ow ¶42).
Ow does not expressly disclose the engagement rules comprise a trusted relationship log that records a relationship status existing between the first customer and each of the entities, wherein, as part of the relationship status, the trusted relationship log comprises data describing: a subset of the personal data of the first customer that is permitted to be shared with each of the entities; and circumstances under which the sharing of the subset of the personal data is permitted with each of the entities.
However, Schur teaches the engagement rules comprise a trusted relationship log that records a relationship status existing between the first customer and each of the entities, wherein, as part of the relationship status, the trusted relationship log comprises data describing: a subset of the personal data of the first customer that is permitted to be shared with each of the entities; and circumstances under which the sharing of the subset of the personal data is permitted with each of the entities (identifies and provides trust for user profiles, social and collaboration networking with an intelligent personal assistant and relation manager that respects selected privacy and tracks information distribution to selected sharing levels, Schur ¶67-¶71; automatically recorded, ¶60; relationship extraction, ¶112).
Both the Ow and Schur references are analogous in that both are directed towards/concerned with automating personal assistance. Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Schur’s method of automated sharing based upon trust sharing levels in Ow’s system to improve the system and method with reasonable expectation that this would result in a personal assistance management system that is more secure.
The motivation being that there is a need for a secure and trusted network in order to improve multiparty collaboration such as users and service providers (Schur ¶50).
The combination of Ow and Schur do not expressly disclose generating, by the computer system, a second predictor from an analysis of a database of customer information of customers different from the first customer, in which the customer information includes aggregated personal profiles generated by the computing system for the customers different from the first customer and is indicative of interactions of the customers with one or more entities and outcomes of interactions, the second predictor generated by applying machine learning to the database of the customer information of customers different from the first customer, including analyzing, with machine learning, the database of customer information indicative of interactions of the customers with the one or more entities and the outcomes of the interactions, identifying, with machine learning, one or more patterns in the customer information in which one or more factors is determined to consistently correlate with a corresponding one of the outcomes, and generating the second predictor as a function of the one or more factors determined to consistently correlate with the corresponding outcome the second predictor relating to a second behavioral factor, and wherein the second predictor is determined to be applicable to a particular subpopulation of customers; determining that the first customer includes a second characteristic having at least a threshold level of similarity to the particular subpopulation of customers; augmenting the customer profile by storing therein the second predictor in response to determining that the first customer includes the second characteristic having at least the threshold level of similarly to the particular subpopulation of customers, wherein the second predictor modifies at least one of the rules of the engagement rules and links the second behavioral factor to the second characteristic; detecting the second characteristic as being present in another incoming transaction; and in response to detecting the second characteristic and without requiring input from the first customer, automatically modifying, in accordance with the second behavioral factor of the second predictor, a manner in which the personal assistant conducts the another incoming transaction on behalf of the first customer.
However, Mazed teaches
generating, by the computer system, a second predictor from an analysis of a database of customer information of customers different from the first customer, in which the customer information includes aggregated personal profiles generated by the computing system for the customers different from the first customer and is indicative of interactions of the customers with one or more entities and outcomes of interactions, the second predictor generated by applying machine learning to the database of the customer information of customers different from the first customer, including analyzing, with machine learning, the database of customer information indicative of interactions of the customers with the one or more entities and the outcomes of the interactions, identifying, with machine learning, one or more patterns in the customer information in which one or more factors is determined to consistently correlate with a corresponding one of the outcomes, and generating the second predictor as a function of the one or more factors determined to consistently correlate with the corresponding outcome the second predictor relating to a second behavioral factor, and wherein the second predictor is determined to be applicable to a particular subpopulation of customers (predictive algorithm in the social wallet to determine relevant users, Mazed ¶94-¶95; personal score of user, ¶77; set of relevant users that meet a predetermined %, ¶94-¶97; As the social wallet 100 can learn or relearn the user's preferences, the unified algorithm 320 can render intelligence based on the user's preferences utilizing the intelligence rendering algorithm 400 and the self-learning (including relearning) algorithm 420, ¶184; accelerate smart automated transactions, ¶60; continuously analyzing patterns of data, using artificial intelligence, neural networks, ¶153-¶155; see also ¶55 discussing the use of machine learning algorithms) (Examiner interprets the ability to determine subsets of relevant users based upon the social profiles as a threshold thereof and social wallets for which to conduct actions or transactions as the ability to generate a second predictor determined to be applicable to a subpopulation of customers for which automated actions can occur based upon incoming transactions or interactions);
determining that the first customer includes a second characteristic having at least a threshold level of similarity to the particular subpopulation of customers; augmenting the customer profile by storing therein the second predictor in response to determining that the first customer includes the second characteristic having at least the threshold level of similarly to the particular subpopulation of customers, wherein the second predictor modifies at least one of the rules of the engagement rules and links the second behavioral factor to the second characteristic; detecting the second characteristic as being present in another incoming transaction; and in response to detecting the second characteristic and without requiring input from the first customer, automatically modifying, in accordance with the second behavioral factor of the second predictor, a manner in which the personal assistant conducts the another incoming transaction on behalf of the first customer (predictive algorithm in the social wallet to determine relevant users, Mazed ¶94-¶95; personal score of user, ¶77; set of relevant users that meet a predetermined %, ¶97; As the social wallet 100 can learn or relearn the user's preferences, the unified algorithm 320 can render intelligence based on the user's preferences utilizing the intelligence rendering algorithm 400 and the self-learning (including relearning) algorithm 420, ¶184; accelerate smart automated transactions, ¶60; see also ¶55 discussing the use of machine learning algorithms) (Examiner interprets the ability to determine subsets of relevant users based upon the social profiles as a threshold thereof and social wallets for which to conduct actions or transactions as the ability to generate a second predictor determined to be applicable to a subpopulation of customers for which automated actions can occur based upon incoming transactions or interactions).
The Ow, Schur, and Mazed references are analogous in that both are directed towards/concerned with automating personal assistance. Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Mazed’s method of providing context aware automation including identifying subsets of relevant users, in Schur and Ow’s system to improve the system and method with reasonable expectation that this would result in a personal assistance management system that is able to provide more accurate predictions for users.
The motivation being that Social networking is no longer just about making social connections online. User experience can be enhanced not only by connecting with people, but also by connecting with information (preferably real time information) and communicating with the object/array of objects. The cornerstone of today's electronic commerce is based on converting a probable click (in a search engine) into an actual sale. By synthesizing social networking with the electronic commerce, one can deliver consistent user experience across all touch-points (e.g., social, mobile and in-store) (Mazed ¶11-¶13).
In addition, the Examiner asserts that claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are: (A) "adapted to" or "adapted for" clauses; (B) "wherein" clauses; and (C) "whereby" clauses (See MPEP 2111.04). In the instant case, the recited “so to maximize an anonymity of the first customer relative to the entities by limiting a disclosure of personally identifiable information of the first customer stored in the customer profile; so that the anonymity of the first customer is maximized " is not a positive method step as it do not require any actual positive recited claim steps to be performed; nor does it modify any of the positively claimed method steps. Similarly, the recited wherein clause is not a positive system element since it doesn’t structurally limit the system and merely describes the intended use of the system and/or the intended result of the use of the system.
Still further, Furthermore, one of ordinary skill, before the effective filing date of the claimed invention, would have found it obvious to repeat the processes in claims 1 and 11 for second or additional predictors relating to a second or additional behavioral factors because duplication is obvious, MPEP 2144.04.VI.B. The duplication of parts (or steps) has no patentable significance unless a new and unexpected result is produced. Examiner finds no evidence that performing the processes in claims 1 and 11 for second or additional predictors relating to a second or additional behavioral factors would produce new and unexpected results as compared to performing the processes in claims 1 and 11 for only a first behavioral predictor relating to a first behavioral factor.
As per claims 3 and 13, Ow, Schur, and Mazed disclose as shown above with respect to claims 2 and 12. Ow further discloses wherein the incoming transaction relates to booking a hotel room (This vault (similar to a digital wallet) will be controlled by keys that the user/owner of the identification can share at their discretion to enable others to positively identify the user/owner for the purpose of transactions requiring such identification. The vault will exist on the user/owner controlled device(s) and may be backed-up to ensure integrity of the identity. As third-parties are allowed to verify the identity of the user/owner, these verification authorizations and confirmations will also be stored in the user identity vault to further add to the validity and authenticity of the user/owner identity , Ow ¶51; In a preferred embodiment, the witness mirror blocks created on the witness private chain during a witness event contain encrypted information which prevents the user of the witness node from seeing any private or personal details from the subject transaction. Details such as party names, items being bought or sold, the pricing of the subject items, vendor names, and other private details of the transaction are encrypted to protect the privacy of the parties that participated in the subject transaction. However, in order for the witness function to perform properly, this information is shared (in an encrypted format) with each witness performing the consensus algorithm via the witness function. Once the witness event is complete (regardless of whether the transaction was authorized or declined) the blocks added to the witness ledger will be encrypted to protect the privacy of the participants of the subject transaction, Ow ¶42; lifestyle events, ¶36-¶37) (Examiner interprets the lifestyle events to include a hotel booking).
The Examiner also notes that the data identifying the transaction (such as a hotel booking, grocery store purchase, medicine) is simply a label for the components and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of transaction) which does not explicitly alter or impact the steps of the method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
As per claims 4 and 14, Ow, Schur, and Mazed disclose as shown above with respect to claims 1 and 11. Ow further discloses wherein the secure data vault is secured via block chain technology; wherein the secure data vault is accessible only by the personal assistant (The AXEL blockchain will also provide a user-focused artificial intelligence (AI) component that will collect and parse transactional data on behalf of the user to give them instant access to information that was transacted utilizing the AXEL blockchain. Transactional information such as automobile maintenance schedules, medical history records, prescription drug records, and other lifestyle events can be processed and tracked through the AI functions of the AXEL blockchain. In one preferred embodiment, the AXEL blockchain AI component will collect and parse information pertaining to the history of a specific user to enable the user to instantly access information including but not limited to medical records, prescription medication history, car maintenance history, general sale and purchase history and other lifestyle metrics that can be managed and tracked through the private ledger and parsed with the artificial intelligence module. The information will be provided to the user based on a query submitted by the user pertaining to their transactional history within the AXEL blockchain. The purpose of the AI and the data parsing is to further enable the users of the AXEL blockchain to accurately track transactional history and provide feedback and historical information directly to the users of the AXEL blockchain. The AXEL blockchain AI component will act as a personal assistant or personal transaction manager for the user to enable them to easily recall historical information pertaining to transactions within the AXEL blockchain. In a preferred embodiment, the AI component is not intended or designated for use by any company or other entity seeking to collect user information for marketing or other purposes. The information may be stored and parsed at a local level to ensure the security and privacy of the AI functionality, Ow ¶36-¶38; belong to a distributed database, ¶293).
Shur further teaches wherein the modified at least one of the rules of the engagement rules further designates that, in relation to the product domain, a consideration of a brand of the preferred brand is more important than a consideration of price in relation to the incoming transaction (facilitates the trusted exchange of goods and services between suppliers and end users, Shur ¶50; According to an embodiment, the present invention enables internal procedures to become sharable to others, enables users to connect with trusted clients, and, protected procedures such as banking and legal procedures, enhances the secrecy of services by enabling cryptography and non-traceability. According to an embodiment, the present invention is also adoptable by supply chain manager. According to an embodiment, the platform of the present invention includes four user categories and seven trust level categories. It is noted, however, that the platform may include any suitable number of categories and/or trust levels. According to an embodiment, the first user category includes daily public users, the second user category includes professionals (e.g., lawyers, doctors etc.), the third user category includes service providers, and the fourth user category includes private companies and institutions, ¶75-¶77) (Examiner notes the trust level associated with a supplier/service provider/professional as the ability to consider a brand of the preferred brands being more important that price in relation to an incoming transaction).
Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Schur’s method of automated sharing based upon trust sharing levels in Ow’s system to improve the system and method with reasonable expectation that this would result in a personal assistance management system that is more secure.
The motivation being that there is a need for a secure and trusted network in order to improve multiparty collaboration such as users and service providers (Schur ¶50).
As per claims 8 and 18, Ow, Schur, and Mazed disclose as shown above with respect to claims 1 and 11. Mazed further teaches wherein the entities comprise companies that produce products; wherein the behavioral factors comprise at least one of: preferences of the first customer; and interests of the first customer; further comprising: receiving marketing messages from the respective companies; filtering the marketing messages based the behavioral factors so to derive a filtered set of marketing messages; and presenting the filtered set of marking messages to the first customer (As the social wallet 100 can learn or relearn the user's preferences, the unified algorithm 320 can render intelligence based on the user's preferences utilizing the intelligence rendering algorithm 400 and the self-learning (including relearning) algorithm 420, Mazed ¶184; Furthermore, in step 4052, the unified algorithm 320 (in particular the predictive algorithm 380) in the social wallet 100 can initially determine a set of relevant users for a targeted advertisement for a specified product and/or service, ¶94).
As per claims 9 and 19, Ow, Schur, and Mazed disclose as shown above with respect to claims 1 and 11. Mazed further teaches generating, by the personal assistant, one or more user interfaces on a display of the communication device that prompt the first customer for input regarding a clarification related to one of the preferences or one of the interests; receiving, by the personal assistant, input from the first customer related to the clarification; and updating, by the automated assistant, the customer profile in accordance with the input received from the first customer (The user 160 could type/talk with the social wallet 100 via the mobile internet appliance 300: “Hi, should I renegotiate my car lease?” Instead of a search result, a lease bot enhanced by the unified algorithm 320 would pop up suggesting a better deal and close it for the user 160 in exchange for a small commission, ¶52; passively listen, respond to a particular context, ¶178).
As per claim 24, Ow, Schur, and Mazed disclose as shown above with respect to claim 11. Mazed further teaches monitoring, by the personal agent, an interaction between the first customer and an entity; identifying, by the personal agent and within the monitored interaction, a conclusory statement made by the first customer at a conclusion of the monitored interaction; analyzing, by the personal agent and with natural language processing, the conclusory statement to determine inferred customer feedback from the conclusory statement; and storing, by the personal agent, the inferred customer feedback in the customer profile of the first customer (In step 4029, the unified algorithm 320 in the social wallet 100 can estimate the personal score of the user 160 by analyzing the profile, message history, chat history and data patterns (including purchase patterns). In step 4030, the unified algorithm 320 in the social wallet 100 can set the personal score of the user 160. The personal score of the user 160 can vary with time. In step 4031, the social wallet 100 can record the personal score of the user 160 over time, Mazed ¶77; natural language processing, ¶152).
Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Mazed’s method of providing context aware automation including identifying subsets of relevant users, in Schur and Ow’s system to improve the system and method with reasonable expectation that this would result in a personal assistance management system that is able to provide more accurate predictions for users.
The motivation being that Social networking is no longer just about making social connections online. User experience can be enhanced not only by connecting with people, but also by connecting with information (preferably real time information) and communicating with the object/array of objects. The cornerstone of today's electronic commerce is based on converting a probable click (in a search engine) into an actual sale. By synthesizing social networking with the electronic commerce, one can deliver consistent user experience across all touch-points (e.g., social, mobile and in-store) (Mazed ¶11-¶13).
Claim 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ow et al. (US PG Pub. 2019/0324958), Schur (US PG Pub. 2019/0205148), Mazed (US PG Pub. 2017/0221032), and further in view of Mueller et al. (US PG Pub. 2020/0151583).
As per claim 21, Ow, Schur, and Mazed disclose as shown above with respect to claim 1. The combination of Ow, Schur, and Mazed do not expressly disclose automatically navigating, by the personal agent and based on a stored script, an interactive voice response (IVR) system on behalf of the first customer and without interacting with the first customer.
However, Mueller teaches automatically navigating, by the personal agent and based on a stored script, an interactive voice response (IVR) system on behalf of the first customer and without interacting with the first customer (interactive voice response system, Meuller Abstract; clarifying concerns, attentive dialog, verifying facts, ¶29; chatbot interface, ¶62).
The Ow, Schur, Mazed, and Mueller references are analogous in that both are directed towards/concerned with automating personal assistance. Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Mueller’s ability to include chatbot functionality, including an interactive voice response system in Mazed, Schur, and Ow’s system to improve the system and, method with reasonable expectation that this would result in a personal assistance management system that is able to provide more accurate predictions for users.
The motivation being that there is a need for addressing explicitly stated customer needs and intentions, inferring customer needs and intentions not explicitly stated by the customer, verifying correctness of information stated by the customer, correcting misconceptions of the customer, paraphrasing and summarizing customer statements, elaborating upon customer statements, adjusting language to conform to the customer's language, using tactful language expressions, helping the customer by suggesting language, providing information about the problem-solving activity of the agent, providing explanations as to why the agent is asking something, providing explanations for what the agent is doing, performing tactfulness assessment on all utterances to ensure that they maintain a positive customer experience, assessing the potential consequences of all utterances, brainstorming diverse solutions with the customer, expressing cognitive and attentive empathy, acknowledging personal information provided by the customer, providing solutions to the customer, retrieving information for the customer, and/or executing transactions on behalf of the customer (Mueller ¶15).
As per claim 22, Ow, Schur, and Mazed disclose as shown above with respect to claim 1. The combination of Ow, Schur, and Mazed do not expressly disclose automatically interacting, by the personal agent and based on a stored script, a contact center agent on behalf of the first customer and without interacting with the first customer.
However, Mueller teaches automatically interacting, by the personal agent and based on a stored script, a contact center agent on behalf of the first customer and without interacting with the first customer (A voice interface is configured to generate audible speech such that an attentive dialogue agent 108 may engage in conversations with another party. The agent interface 106 may further convert received speech to text (e.g., based on a known language processing algorithm (not separately shown) to facilitate the ability of the system 100 to engage in attentive dialogue. As such, the system 100 may be configured to operate without human participation within system 100, while engaging human input from the customer, received over the network 130, Mueller ¶20).
The Ow, Schur, Mazed, and Mueller references are analogous in that both are directed towards/concerned with automating personal assistance. Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Mueller’s ability to include chatbot functionality, including an interactive voice response system in Mazed, Schur, and Ow’s system to improve the system and, method with reasonable expectation that this would result in a personal assistance management system that is able to provide more accurate predictions for users.
The motivation being that there is a need for addressing explicitly stated customer needs and intentions, inferring customer needs and intentions not explicitly stated by the customer, verifying correctness of information stated by the customer, correcting misconceptions of the customer, paraphrasing and summarizing customer statements, elaborating upon customer statements, adjusting language to conform to the customer's language, using tactful language expressions, helping the customer by suggesting language, providing information about the problem-solving activity of the agent, providing explanations as to why the agent is asking something, providing explanations for what the agent is doing, performing tactfulness assessment on all utterances to ensure that they maintain a positive customer experience, assessing the potential consequences of all utterances, brainstorming diverse solutions with the customer, expressing cognitive and attentive empathy, acknowledging personal information provided by the customer, providing solutions to the customer, retrieving information for the customer, and/or executing transactions on behalf of the customer (Mueller ¶15).
As per claim 23, Ow, Schur, Mazed, and Mueller disclose as shown above with respect to claim 22. Mueller further teaches wherein automatically interacting with the contact center agent comprises: determining, by the personal agent, that a particular response of the contact center agent is not stored in a dialogue tree of the personal agent; and requesting, by the personal agent, the contact center agent to rephrase the response in response to determining that the particular response is not stored in the dialogue tree (interactive voice response system, Meuller Abstract; clarifying concerns, attentive dialog, verifying facts, ¶29; chatbot interface, ¶62).
Claim 25-26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ow et al. (US PG Pub. 2019/0324958), Schur (US PG Pub. 2019/0205148), Mazed (US PG Pub. 2017/0221032), and further in view of Bhaya et al. (US PG Pub. 20180247654).
As per claim 25, Ow, Schur, and Mazed disclose as shown above with respect to claim 1. The combination of Ow, Schur, and Mazed do not expressly disclose generating, by the personal agent and based on the engagement rules, a virtual identity token indicative of contact information to enable anonymously completing a transaction with an entity on behalf of the first customer; completing, by the personal agent, the transaction on behalf of the first customer; and disposing of the virtual identity token, by the personal agent, in response to completion of the transaction.
However, Bhaya teaches generating, by the personal agent and based on the engagement rules, a virtual identity token indicative of contact information to enable anonymously completing a transaction with an entity on behalf of the first customer; completing, by the personal agent, the transaction on behalf of the first customer; and disposing of the virtual identity token, by the personal agent, in response to completion of the transaction (virtual identifiers, virtual tokens, Bhaya ¶18; token based on device identifier, ¶117; example scenario, shopping, electronic payment, ¶81; tokens maintain anonymity, ¶123).
The Ow, Schur, Mazed, and Bhaya references are analogous in that both are directed towards/concerned with automating personal assistance. Before the time of the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Bhaya’s ability to use tokenized device identifiers in Mazed, Schur, and Ow’s system to improve the system and, method with reasonable expectation that this would result in a personal assistance management system that is able to provide more secure, accurate predictions for users.
The motivation being that the excessive network transmissions of network traffic data can also complicate data routing or degrade the quality of the response if the responding computing device is at or above its processing capacity, which may result in inefficient bandwidth utilization. The control of network transmissions corresponding to content item objects can be complicated by the large number of content item objects that can initiate network transmissions of network traffic data between computing devices (Bhaya ¶2).
As per claim 26, Ow, Schur, Mazed, and Bhaya disclose as shown above with respect to claim 25. Bhaya further teaches wherein generating a virtual identity token comprises generating one or more of a phone number or an email address (token based on device identifier, Bhaya ¶117).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to ANDREW B WHITAKER whose telephone number is (571)270-7563. The examiner can normally be reached on M-F, 8am-5pm, EST.
If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Lynda Jasmin can be reached on (571) 272-6782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW B WHITAKER/Primary Examiner, Art Unit 3629
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