Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
2. 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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-17 of U.S. Patent No. 12154084. Although the claims at issue are not identical, they are not patentably distinct from each other. A mapping between the limitations of these claims is provided below.
Instant Application
Issued Patent
1. A system comprising: a processing device; and a non-transitory computer-readable memory that is executable by the processing device to perform operations comprising:
generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application;
receiving a request via the interactive channel;
receiving location information from a personal device associated with the request;
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device;
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI;
generating a set of updated guided options based at least in part on the one or more visualization tools; and
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request.
2. The system of claim 1, wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device remote from the system, and
wherein the plurality of guided options are providable by the GUI based at least in part on a pending transaction.
3. The system of claim 2, wherein the operation of generating the insight comprises: retrieving historical data about a second party;
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party; and
transmitting a result of the statistical analysis via the GUI.
4. The system of claim 1, wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party,
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
5. The system of claim 1, wherein the operations further comprise: transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools; and
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options.
6. The system of claim 1, wherein the operations further comprise generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generatable.
7. The system of claim 6, wherein the operations further comprise receiving a request from the second party that is associated with the guided options.
8. A computer-implemented method comprising: generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application;
receiving a request via the interactive channel;
receiving location information from a personal device associated with the request;
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device;
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that provide the insight graphically on the GUI;
generating a set of updated guided options based at least in part on the one or more visualization tools; and
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request.
9. The method of claim 8, wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device, and
wherein the plurality of guided options are provided by the GUI based at least in part on a pending transaction.
10. The computer-implemented method of claim 9, wherein generating the insight comprises:
retrieving historical data about a second party;
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party; and
transmitting a result of the statistical analysis via the GUI.
11. The computer-implemented method of claim 8, wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party, and
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
12. The computer-implemented method of claim 8, further comprising: transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools; and
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options.
13. The computer-implemented method of claim 8, further comprising generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generated.
14. The computer-implemented method of claim 13, further comprising receiving a request from the second party that is associated with the guided options.
15. A non-transitory computer-readable medium comprising program code that is executable by one or more processors for causing the one or more processors to perform operations comprising:
generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application;
receiving a request via the interactive channel;
receiving location information from a personal device associated with the request;
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device;
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI;
generating a set of updated guided options based at least in part on the one or more visualization tools; and
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request.
16. The non-transitory computer-readable medium of claim 15, wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device, and
wherein the plurality of guided options are providable by the GUI based at least in part on a pending transaction.
17. The non-transitory computer-readable medium of claim 16, wherein the operation of generating the insight comprises: retrieving historical data about a second party;
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party; and
transmitting a result of the statistical analysis via the GUI.
18. The non-transitory computer-readable medium of claim 15, wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party,
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
19. The non-transitory computer-readable medium of claim 15, wherein the operations further comprise: transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools; and
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options.
20. The non-transitory computer-readable medium of claim 15, wherein the operations further comprise generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generatable.
(claim 1) A system comprising: a processing device; and a non-transitory computer-readable memory that is executable by the processing device to perform operations comprising:
(claim 1) generating an interactive channel by a first party that comprises a virtual assistant to provide a plurality of guided options to a second party via a graphical user interface (GUI) in a mobile banking application,
(claim 1) receiving a request, via the interactive channel, from the second party;
(claim 1) receiving location information from a personal device associated with the second party;
(claim 1) determining an intent of the request from the second party by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile banking application and (ii) the location information from the personal device of the second party;
(claim 1) generating an insight based on the determined intent of the request and a user profile of the second party, the insight comprising a cash flow and spending summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI;
(claim 1) generating a set of updated guided options based at least in part on an interaction with the one or more visualization tools;
(claim 1) arranging the set of updated guided options on the GUI in descending order of likelihood of relevance, based on the interaction, to the second party;
(claim 2) wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device remote from the system
(claim 1) the plurality of guided options providable by the GUI based at least in part on a pending transaction involving the second party
(claim 3) wherein the operation of generating the insight based on the intent of the request and the user profile of the second party comprises: retrieving historical data about the second party;
(claim 3) performing statistical analysis based on the historical data, the intent of the request, and the user profile of the second party; and
(claim 3) transmitting a result of the statistical analysis via the GUI.
(claim 4) wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between the first party and the second party,
(claim 4) wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
(claim 1) transmitting the insight, via the interactive channel, to the second party, the transmitting comprising populating the GUI with the one or more visualization tools;
(claim 1) initiating the pending transaction based at least in part on subsequent input, based on the set of updated guided options, from the second party.
(claim 5) wherein the operations further comprise: generating the guided options based on historical data and the user profile of the second user.
(claim 6) wherein the request received from the second party is associated with the guided options.
(claim 7) A computer-implemented method comprising: generating an interactive channel by a first party that comprises a virtual assistant to provide a plurality of guided options to a second party via a graphical user interface (GUI) in a mobile banking application,
(claim 7) receiving a request, via the interactive channel, from the second party;
(claim 7) receiving location information from a personal device associated with the second party;
(claim 7) determining an intent of the request from the second party by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile banking application and (ii) the location information from the personal device of the second party;
(claim 7) generating an insight based on the determined intent of the request and a user profile of the second party, the insight comprising a cash flow and spending summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI;
(claim 7) generating a set of updated guided options based at least in part on an interaction with the one or more visualization tools;
(claim 7) arranging the set of updated guided options on the GUI in descending order of likelihood of relevance, based on the interaction, to the second party
(claim 8) wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device
(claim 7) the plurality of guided options providable by the GUI based at least in part on a pending transaction involving the second party
(claim 9) wherein generating the insight based on the intent of the request and the user profile of the second party comprises:
(claim 9) retrieving historical data about the second party;
(claim 9) performing statistical analysis based on the historical data, the intent of the request, and the user profile of the second party; and
(claim 9) transmitting a result of the statistical analysis via the GUI.
(claim 10) wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between the first party and the second party,
(claim 10) wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
(claim 7) transmitting the insight, via the interactive channel, to the second party, the transmitting comprising populating the GUI with the one or more visualization tools
(claim 7) initiating the pending transaction based at least in part on subsequent input, based on the set of updated guided options, from the second party
(claim 11) generating the guided options based on historical data and the user profile of the second user
(claim 12) wherein the request received form the second party is associated with the guided options.
(claim 13) A non-transitory computer-readable medium comprising program code that is executable by one or more processors for causing the one or more processors to perform operations comprising:
(claim 13) generating an interactive channel by a first party that comprises a virtual assistant to provide a plurality of guided options to a second party via a graphical user interface (GUI) in a mobile banking application,
(claim 13) receiving a request, via the interactive channel, from the second party;
(claim 13) receiving location information from a personal device associated with the second party;
(claim 13) determining an intent of the request from the second party by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile banking application and (ii) the location information from the personal device of the second party;
(claim 13) generating an insight based on the determined intent of the request and a user profile of the second party, the insight comprising a cash flow and spending summary for a predetermined time period that is prior to receiving the request, and the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI;
(claim 13) generating a set of updated guided options based at least in part on an interaction with the one or more visualization tools;
(claim 13) arranging the set of updated guided options on the GUI in descending order of likelihood of relevance, based on the interaction, to the second party
(claim 14) wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device
(claim 13) the plurality of guided options providable by the GUI based at least in part on a pending transaction involving the second party
(claim 15) wherein the operation of generating the insight based on the intent of the request and the user profile of the second party comprises: retrieving historical data about the second party;
(claim 15) performing statistical analysis based on the historical data, the intent of the request, and the user profile of the second party; and
(claim 15) transmitting a result of the statistical analysis via the GUI.
(claim 16) wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between the first party and the second party,
(claim 16) wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party.
(claim 13) transmitting the insight, via the interactive channel, to the second party, the transmitting comprising populating the GUI with the one or more visualization tools
(claim 13) initiating the pending transaction based at least in part on subsequent input, based on the set of updated guided options, from the second party.
(claim 17) wherein the operations further comprise: generating the guided options based on historical data and the user profile of the second user.
Therefore, because claims 1-17 the issued patent teach each limitation of claims 1-20 of the instant application, claims 1-20 of the instant application are anticipated by claims 1-17 of the issued patent.
Claim Rejections - 35 USC § 103
3. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
4. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Pace (U.S. Patent No. 11212241) in view of Hoover (U.S. Patent No. 10783876), Walters (U.S. Patent No. 11748806), and Gabbai (U.S. Pre-Grant Publication No. 20150242928).
Claim 1
Regarding Claim 1, Pace teaches:
A system comprising: a processing device (See at least Col. 4, Lines 39-51: Describes a system comprising a virtual device platform [i.e., a processing device]); and
a non-transitory computer-readable memory that is executable by the processing device to perform operations comprising (See at least Col. 3, Lines 51-67: The system also comprises a machine-readable medium storing instructions):
generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application (See at least Paragraphs 45-46: A communication session [i.e., an interactive channel] is established over a network between the users [i.e., the second party] and virtual assistants [i.e., the first party] associated with the platform. The platform may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Paragraph 66 and Figure 6D, 655]);
receiving a request via the interactive channel (See at least Paragraph 47: the virtual advice platform receives, via a chatbot or other virtual assistant of an information services platform located at a server, a message over a communications network from a mobile device associated with a user that is a member of an entity providing the information services platform);
determining an intent of the request by [[a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device]] (See at least Paragraph 50: the platform determines and/or identifies a question within the message received from the mobile device. Also see Paragraph 22: The platform may receive messages from one or more devices, extract, parse, or otherwise obtain a question or other similar intent from within the messages [i.e., the question identified by the system may be associated with an intent of the user]. Examiner’s Note: Pace does not explicitly teach that a machine learning model is used to determine the intent of the user using a natural language process or and location data. However, Hoover does teach this limitation as described below);
generating an insight based on the determined intent of the request, [[the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request]] (See at least Paragraphs 53-54: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user and based on the questions posed by the user. The simulation may provide an “insight” regarding the question posed by the user [e.g., simulating how the user's future net worth change should the user buy a car at a certain price today]. The simulation may also utilize accessed information associated with the user. The user information may be stored in a user profile [See Paragraph 29]. Examiner’s Note: Pace does not explicitly teach that the insight comprises an “interaction summary.” However, this limitation is disclosed by Walters as described below), and
the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI (See at least Paragraph 59: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The content of the message to the user can further include a result of the performed one or more simulations. In other words, the result of the simulation [i.e., the insight] is displayed graphically on the mobile device); and
generating a set of updated guided options based at least in part on the one or more visualization tools (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation [i.e., a set of updated guided options]. For example, the platform may notify the user that they can likely afford a particular transaction); and
Regarding Claim 1, Pace does not explicitly teach, but Hoover, however, does teach:
receiving location information from a personal device associated with the request (See at least Col. 29, Line 61 – Col. 30, Line 19: Describes a system for determining the intent of a request provided by a user. The natural language component may receive location data associated with the device in order to assist in determining the intent of the request); and
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device (See at least Col. 29, Line 61 – Col. 30, Line 19: The system may utilize machine learning techniques and a natural language component [i.e., a natural language processing engine] in order to determine the intent of the request [Also see Col. 11, Lines 1-27]. The natural language component may use the location data to assist in determining the intent).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace and Hoover in order to take improve interactions between humans and computers by applying natural language processing techniques to determine the intent of a user request (Walters: Col. 1, Lines 6-19 and Col. 29, Line 61 – Col. 30, Line 19).
Regarding Claim 1, the combination of Pace and Hoover does not explicitly teach, but Walters, however, does teach:
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request (See at least Col. 7, Line 50 – Col. 8, line 2: Describes a system for controlling spending by a customer. The system may generate a graphic [i.e., an insight] that describes a user’s spending over a period of time [See Figures 3 and 4]. This may be done before receiving a purchase request from the user [See Col. 10, Line 38 – Col. 11, Line 10]. Examiner’s Note: The term “interaction summary” does not appear to be explicitly defined, or even mentioned, in the applicant’s specification. However, this term has been interpreted according to Paragraph 16 of the applicant’s specification which states that the insight may be related to a “spending summary at a particular month, date or time.” The “interaction summary” has been interpreted as referring to the "spending summary"18escrybed in the specificat“on).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, and Walters in order to provide a user control over credit or debit card purchases. This prevents excessive impulse spending without rational reasoning (Walters: Col. 1, Lines 45-58).
Regarding Claim 1, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request (See at least Paragraph 55: Describes a system for recommending products to a user. The ranked list of products may be communicated to the client device which may display the ranked list of product listings in order of relevance to the user).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 2
Regarding Claim 2, Pace teaches:
wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device remote from the system (See at least Col. 5, Lines 22-37: The user device may display a messaging interface [e.g., see Figures 6A-6D] for facilitating communication between the user and the virtual assistant); and
wherein the plurality of guided options are providable by the GUI based at least in part on a pending transaction (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation. For example, the platform may notify the user that they can likely afford a particular transaction [e.g., a pending transaction]).
Claim 3
Regarding Claim 3, Pace teaches:
wherein the operation of generating the insight comprises: retrieving historical data about a second party (See at least Col. 9, Lines 53-63: The platform may obtain information from a variety of different accounts or services managed and/or provided by an entity, such as a financial services entity, providing the platform. Example information includes biographical information and financial history information associated with the user);
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party (See at least Col. 9, Line 64 – Col. 10, line 13: The simulation module of the simulation agent may perform one or more simulations [i.e., statistical analysis] using the accessed information associated with the user and based on the questions posed by the user); and
transmitting a result of the statistical analysis via the GUI (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The messages are displayed through a messaging interface of the user device [See Figures 6A-6D]).
Claim 4
Regarding Claim 4, Pace teaches:
wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party (See at least Figure 6A: The chat interface comprises an area where the user may type text for the message that is sent to the virtual assistant [i.e., an insertion box]. The messages sent between the user and the virtual assistant are displayed above the text box [i.e., in a dialogue text box]);
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party (See at least Figure 6A: The user may provide text input via the messaging interface. Examiner’s Note: Pace does not explicitly state that the messaging interface is a touchscreen. However, it would have been obvious to one of ordinary skill in the art that the keyboard within the mobile device interface displayed in Figure 6A receives touch input from the user to receive text).
Claim 5
Regarding Claim 5, Pace teaches:
wherein the operations further comprise: transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message).
Regarding Claim 5, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options (See at least Paragraphs 64-66: The user may select a recommended product to initiate a purchase request for the selected product).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 6
Regarding Claim 6, Pace teaches:
wherein the operations further comprise generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generatable (See at least Col. 9, Line 64 – Col. 10, Line 13: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user [i.e., information from a user profile and historical information; See Col. 6, Lines 15-37 and Col. 9, Lines 53-63] and based on the questions posed by the user. Additionally, the results of the simulation may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Col. 11, Lines 29-35 and Figure 6D, 655]).
Claim 7
Regarding Claim 7, Pace teaches:
wherein the operations further comprise receiving a request from the second party that is associated with the guided options (See at least Col. 11, Lines 6-35: The option presented to the user is associated with the question provided by the user. For example, the user may present a question stating, “I want to buy a car.” The option provided to the user may comprise a link to a program offered by the platform for saving for the vehicle).
Claim 8
Regarding Claim 8, Pace teaches:
A computer-implemented method comprising: generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application (See at least Paragraphs 45-46: A communication session [i.e., an interactive channel] is established over a network between the users [i.e., the second party] and virtual assistants [i.e., the first party] associated with the platform. The platform may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Paragraph 66 and Figure 6D, 655]);
receiving a request via the interactive channel (See at least Paragraph 47: the virtual advice platform receives, via a chatbot or other virtual assistant of an information services platform located at a server, a message over a communications network from a mobile device associated with a user that is a member of an entity providing the information services platform);
determining an intent of the request by [[a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device]] (See at least Paragraph 50: the platform determines and/or identifies a question within the message received from the mobile device. Also see Paragraph 22: The platform may receive messages from one or more devices, extract, parse, or otherwise obtain a question or other similar intent from within the messages [i.e., the question identified by the system may be associated with an intent of the user]. Examiner’s Note: Pace does not explicitly teach that a machine learning model is used to determine the intent of the user using a natural language process or and location data. However, Hoover does teach this limitation as described below);
generating an insight based on the determined intent of the request, [[the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request]] (See at least Paragraphs 53-54: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user and based on the questions posed by the user. The simulation may provide an “insight” regarding the question posed by the user [e.g., simulating how the user's future net worth change should the user buy a car at a certain price today]. The simulation may also utilize accessed information associated with the user. The user information may be stored in a user profile [See Paragraph 29]. Examiner’s Note: Pace does not explicitly teach that the insight comprises an “interaction summary.” However, this limitation is disclosed by Walters as described below), and
the insight comprising one or more visualization tools that provide the insight graphically on the GUI (See at least Paragraph 59: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The content of the message to the user can further include a result of the performed one or more simulations. In other words, the result of the simulation [i.e., the insight] is displayed graphically on the mobile device); and
generating a set of updated guided options based at least in part on the one or more visualization tools (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation [i.e., a set of updated guided options]. For example, the platform may notify the user that they can likely afford a particular transaction).
Regarding Claim 8, Pace does not explicitly teach, but Hoover, however, does teach:
receiving location information from a personal device associated with the request (See at least Col. 29, Line 61 – Col. 30, Line 19: Describes a system for determining the intent of a request provided by a user. The natural language component may receive location data associated with the device in order to assist in determining the intent of the request); and
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device (See at least Col. 29, Line 61 – Col. 30, Line 19: The system may utilize machine learning techniques and a natural language component [i.e., a natural language processing engine] in order to determine the intent of the request [Also see Col. 11, Lines 1-27]. The natural language component may use the location data to assist in determining the intent).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace and Hoover in order to take improve interactions between humans and computers by applying natural language processing techniques to determine the intent of a user request (Walters: Col. 1, Lines 6-19 and Col. 29, Line 61 – Col. 30, Line 19).
Regarding Claim 8, the combination of Pace and Hoover does not explicitly teach, but Walters, however, does teach:
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request (See at least Col. 7, Line 50 – Col. 8, line 2: Describes a system for controlling spending by a customer. The system may generate a graphic [i.e., an insight] that describes a user’s spending over a period of time [See Figures 3 and 4]. This may be done before receiving a purchase request from the user [See Col. 10, Line 38 – Col. 11, Line 10]. Examiner’s Note: The term “interaction summary” does not appear to be explicitly defined, or even mentioned, in the applicant’s specification. However, this term has been interpreted according to Paragraph 16 of the applicant’s specification which states that the insight may be related to a “spending summary at a particular month, date or time.” The “interaction summary” has been interpreted as referring to the "spending summary"26escrybed in the specificat“on).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, and Walters in order to provide a user control over credit or debit card purchases. This prevents excessive impulse spending without rational reasoning (Walters: Col. 1, Lines 45-58).
Regarding Claim 8, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request (See at least Paragraph 55: Describes a system for recommending products to a user. The ranked list of products may be communicated to the client device which may display the ranked list of product listings in order of relevance to the user).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 9
Regarding Claim 9, Pace teaches:
wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device (See at least Col. 5, Lines 22-37: The user device may display a messaging interface [e.g., see Figures 6A-6D] for facilitating communication between the user and the virtual assistant); and
wherein the plurality of guided options are providable by the GUI based at least in part on a pending transaction (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation. For example, the platform may notify the user that they can likely afford a particular transaction [e.g., a pending transaction]).
Claim 10
Regarding Claim 10, Pace teaches:
wherein generating the insight comprises: retrieving historical data about a second party (See at least Col. 9, Lines 53-63: The platform may obtain information from a variety of different accounts or services managed and/or provided by an entity, such as a financial services entity, providing the platform. Example information includes biographical information and financial history information associated with the user);
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party (See at least Col. 9, Line 64 – Col. 10, line 13: The simulation module of the simulation agent may perform one or more simulations [i.e., statistical analysis] using the accessed information associated with the user and based on the questions posed by the user); and
transmitting a result of the statistical analysis via the GUI (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The messages are displayed through a messaging interface of the user device [See Figures 6A-6D]).
Claim 11
Regarding Claim 11, Pace teaches:
wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party (See at least Figure 6A: The chat interface comprises an area where the user may type text for the message that is sent to the virtual assistant [i.e., an insertion box]. The messages sent between the user and the virtual assistant are displayed above the text box [i.e., in a dialogue text box]);
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party (See at least Figure 6A: The user may provide text input via the messaging interface. Examiner’s Note: Pace does not explicitly state that the messaging interface is a touchscreen. However, it would have been obvious to one of ordinary skill in the art that the keyboard within the mobile device interface displayed in Figure 6A receives touch input from the user to receive text).
Claim 12
Regarding Claim 12, Pace teaches:
transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message).
Regarding Claim 12, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options (See at least Paragraphs 64-66: The user may select a recommended product to initiate a purchase request for the selected product).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 13
Regarding Claim 13, Pace teaches:
generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generated (See at least Col. 9, Line 64 – Col. 10, Line 13: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user [i.e., information from a user profile and historical information; See Col. 6, Lines 15-37 and Col. 9, Lines 53-63] and based on the questions posed by the user. Additionally, the results of the simulation may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Col. 11, Lines 29-35 and Figure 6D, 655]).
Claim 14
Regarding Claim 14, Pace teaches:
receiving a request from the second party that is associated with the guided options (See at least Col. 11, Lines 6-35: The option presented to the user is associated with the question provided by the user. For example, the user may present a question stating, “I want to buy a car.” The option provided to the user may comprise a link to a program offered by the platform for saving for the vehicle).
Claim 15
Regarding Claim 15, Pace teaches:
A non-transitory computer-readable medium comprising program code that is executable by one or more processors for causing the one or more processors to perform operations comprising (See at least Col. 4, Lines 39-51: Describes a system comprising a virtual device platform [i.e., a processing device]. The system also comprises a machine-readable medium storing instructions [See Col. 3, Lines 51-67]); and
generating an interactive channel comprising a virtual assistant for providing a plurality of guided options via a graphical user interface (GUI) in a mobile application (See at least Paragraphs 45-46: A communication session [i.e., an interactive channel] is established over a network between the users [i.e., the second party] and virtual assistants [i.e., the first party] associated with the platform. The platform may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Paragraph 66 and Figure 6D, 655]);
receiving a request via the interactive channel (See at least Paragraph 47: the virtual advice platform receives, via a chatbot or other virtual assistant of an information services platform located at a server, a message over a communications network from a mobile device associated with a user that is a member of an entity providing the information services platform);
determining an intent of the request by [[a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device]] (See at least Paragraph 50: the platform determines and/or identifies a question within the message received from the mobile device. Also see Paragraph 22: The platform may receive messages from one or more devices, extract, parse, or otherwise obtain a question or other similar intent from within the messages [i.e., the question identified by the system may be associated with an intent of the user]. Examiner’s Note: Pace does not explicitly teach that a machine learning model is used to determine the intent of the user using a natural language process or and location data. However, Hoover does teach this limitation as described below);
generating an insight based on the determined intent of the request, [[the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request]] (See at least Paragraphs 53-54: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user and based on the questions posed by the user. The simulation may provide an “insight” regarding the question posed by the user [e.g., simulating how the user's future net worth change should the user buy a car at a certain price today]. The simulation may also utilize accessed information associated with the user. The user information may be stored in a user profile [See Paragraph 29]. Examiner’s Note: Pace does not explicitly teach that the insight comprises an “interaction summary.” However, this limitation is disclosed by Walters as described below), and
the insight comprising one or more visualization tools that are configured to provide the insight graphically on the GUI (See at least Paragraph 59: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The content of the message to the user can further include a result of the performed one or more simulations. In other words, the result of the simulation [i.e., the insight] is displayed graphically on the mobile device); and
generating a set of updated guided options based at least in part on the one or more visualization tools (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation [i.e., a set of updated guided options]. For example, the platform may notify the user that they can likely afford a particular transaction); and
Regarding Claim 15, Pace does not explicitly teach, but Hoover, however, does teach:
receiving location information from a personal device associated with the request (See at least Col. 29, Line 61 – Col. 30, Line 19: Describes a system for determining the intent of a request provided by a user. The natural language component may receive location data associated with the device in order to assist in determining the intent of the request); and
determining an intent of the request by a machine-learning algorithm using (i) a natural language processing engine or a natural language understanding engine embedded in the mobile application and (ii) the location information from the personal device (See at least Col. 29, Line 61 – Col. 30, Line 19: The system may utilize machine learning techniques and a natural language component [i.e., a natural language processing engine] in order to determine the intent of the request [Also see Col. 11, Lines 1-27]. The natural language component may use the location data to assist in determining the intent).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace and Hoover in order to take improve interactions between humans and computers by applying natural language processing techniques to determine the intent of a user request (Walters: Col. 1, Lines 6-19 and Col. 29, Line 61 – Col. 30, Line 19).
Regarding Claim 15, the combination of Pace and Hoover does not explicitly teach, but Walters, however, does teach:
generating an insight based on the determined intent of the request, the insight comprising an interaction summary for a predetermined time period that is prior to receiving the request (See at least Col. 7, Line 50 – Col. 8, line 2: Describes a system for controlling spending by a customer. The system may generate a graphic [i.e., an insight] that describes a user’s spending over a period of time [See Figures 3 and 4]. This may be done before receiving a purchase request from the user [See Col. 10, Line 38 – Col. 11, Line 10]. Examiner’s Note: The term “interaction summary” does not appear to be explicitly defined, or even mentioned, in the applicant’s specification. However, this term has been interpreted according to Paragraph 16 of the applicant’s specification which states that the insight may be related to a “spending summary at a particular month, date or time.” The “interaction summary” has been interpreted as referring to the "spending summary"34escrybed in the specificat“on).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, and Walters in order to provide a user control over credit or debit card purchases. This prevents excessive impulse spending without rational reasoning (Walters: Col. 1, Lines 45-58).
Regarding Claim 15, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
arranging the set of updated guided options on the GUI in descending order of likelihood of relevance to the request (See at least Paragraph 55: Describes a system for recommending products to a user. The ranked list of products may be communicated to the client device which may display the ranked list of product listings in order of relevance to the user).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 16
Regarding Claim 16, Pace teaches:
wherein the interactive channel comprises a graphical user interface (GUI) displayable on a computing device (See at least Col. 5, Lines 22-37: The user device may display a messaging interface [e.g., see Figures 6A-6D] for facilitating communication between the user and the virtual assistant); and
wherein the plurality of guided options are providable by the GUI based at least in part on a pending transaction (See at least Col. 11, Lines 29-35: The platform may also send a message to the user comprising a saving recommendation. For example, the platform may notify the user that they can likely afford a particular transaction [e.g., a pending transaction]).
Claim 17
Regarding Claim 17, Pace teaches:
wherein the operation of generating the insight comprises: retrieving historical data about a second party (See at least Col. 9, Lines 53-63: The platform may obtain information from a variety of different accounts or services managed and/or provided by an entity, such as a financial services entity, providing the platform. Example information includes biographical information and financial history information associated with the user);
performing statistical analysis based on the historical data, the intent of the request, and a user profile of the second party (See at least Col. 9, Line 64 – Col. 10, line 13: The simulation module of the simulation agent may perform one or more simulations [i.e., statistical analysis] using the accessed information associated with the user and based on the questions posed by the user); and
transmitting a result of the statistical analysis via the GUI (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message. The messages are displayed through a messaging interface of the user device [See Figures 6A-6D]).
Claim 18
Regarding Claim 18, Pace teaches:
wherein the interactive channel comprises a dialogue area and an insertion box, wherein the dialogue area comprises a dialogue text box configured to display a conversation associated with intelligent data transmission between a first party and a second party (See at least Figure 6A: The chat interface comprises an area where the user may type text for the message that is sent to the virtual assistant [i.e., an insertion box]. The messages sent between the user and the virtual assistant are displayed above the text box [i.e., in a dialogue text box]);
wherein the insertion box enables the second party to input text through a touchscreen or a voice receiver of the second party (See at least Figure 6A: The user may provide text input via the messaging interface. Examiner’s Note: Pace does not explicitly state that the messaging interface is a touchscreen. However, it would have been obvious to one of ordinary skill in the art that the keyboard within the mobile device interface displayed in Figure 6A receives touch input from the user to receive text).
Claim 19
Regarding Claim 19, Pace teaches:
wherein the operations further comprise: transmitting the insight via the interactive channel by populating the GUI with the one or more visualization tools (See at least Col. 10, lines 31-41: The platform provides, via the chatbot or virtual assistant, a message to the mobile device. The content of the message to the user can include guidance or advice about the subject matter of the user’s initial message).
Regarding Claim 19, the combination of Pace, Hoover, and Walters does not explicitly teach, but Gabbai, however, does teach:
initiating a pending transaction based at least in part on subsequent input, based on the set of updated guided options (See at least Paragraphs 64-66: The user may select a recommended product to initiate a purchase request for the selected product).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to combine the teachings of Pace, Hoover, Walters, and Gabbai in order to offer consumers a wide variety of goods and services and provide merchants many opportunities to cross sell or up sell related goods and services (Gabbai: Paragraph 2).
Claim 20
Regarding Claim 20, Pace teaches:
wherein the operations further comprise generating the guided options based on historical data and a user profile of a second party associated with a first party by which the interactive channel is generatable (See at least Col. 9, Line 64 – Col. 10, Line 13: The simulation module of the simulation agent may perform one or more simulations using the accessed information associated with the user [i.e., information from a user profile and historical information; See Col. 6, Lines 15-37 and Col. 9, Lines 53-63] and based on the questions posed by the user. Additionally, the results of the simulation may provide options to the user for accessing tools provided by the platform [i.e., guided options; See Col. 11, Lines 29-35 and Figure 6D, 655]).
Citation of Pertinent Prior Art
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Balasubramanian (U.S. Patent No. 9471939): Describes a system for recommending products. The system may display the list of recommended products in relevancy score order to the user.
Lim (U.S. Patent No. 10909124): Describes a computing system that determines, based on user-initiated actions performed by a group of computing devices, an intent of a search using a particular search query received from a computing device.
Conclusion
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/WILLIAM D NEWLON/Examiner, Art Unit 3696
/MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696