Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on June 10, 2026 has been entered.
Response to Amendment
In response to the amendment filed on June 10, 2026:
Claims 1, 3, 13, 14, and 20 are amended.
Claims 1-20 are pending.
Response to Arguments
In response to the remarks filed on June 10, 2026:
35 U.S.C. 103 rejections of the pending claims have been fully considered but are moot in view of a new ground of rejections presented here on.
Notes
Each of independent claims 1, 13, and 20 now recites “intercepting, by one or more processors/first server, a message conveyed between a transmission server and a reception server, the transmission server and the reception server separate from the one or more processors/first server, wherein the transmission server corresponds to a first data store or interface of an enterprise management system, and the reception server corresponds to a second data store or interface of the enterprise management system” which is not directed to abstract idea because they successfully integrate the recited data processing pipeline into a practical application. Each claim recites a specific, internal network architecture that intercepts messages conveyed between a first datastore or interface and a second datastore or interface of an enterprise management system. This specific, non-intrusive “man-in-the-middle” middleware topology solves a recognized technical problem ([0003]-[0004] of instant specification) of harmonization of siloed data across disparate enterprise datastores without requiring reconfiguration or modification of the source systems themselves. By confining the data extraction and entity determination to this specific architectural implementation, each claim proves a concrete technical improvement to the functioning of the enterprise network itself, per step 2A – prong 2 of the abstract idea analysis, rather than merely invoking generic computers as a tool to perform the abstract concept.
Further, per step 2B, each independent claim as a whole recites additional elements that amount to significantly more than the judicial exception. The specific arrangement of components - using a discrete processor separate from the transmission and reception servers to passively intercept internal datastore-to-datastore traffic, extract interaction signals, and dynamically generate and present interaction basis information – is not a well-understood, routine, and conventional (WURC) arrangement in the field of enterprise network routing and monitoring. This specific configuration provides an inventive concept that transform the nature of the claim into a patent eligible application in a non-conventional manner. Thus, claims 1, 13, and 20 and all respective dependent claims are statutory under 35 U.S.C. 101 abstract idea analysis.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 7-10, 12-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Shapira et al. (Pub. No. US 20230144109, published on May 11, 2023; hereinafter Shapira) in view of Webster (Pat. No. US 9319524, published on April 19, 2016).
Regarding claim 1, Shapira clearly shows and discloses a method (Abstract) comprising:
intercepting, by one or more processors, a message conveyed between a transmission server and a reception server (Message brokers may be software applications that implement Publish and Subscribe mechanisms as an effective way of disseminating information to multiple users. Business applications and services connected to a particular message broker are typically written so that a “community” of clients with a common purpose enables them to send and receive messages among themselves. A message broker may be an intermediary acting between publishers and subscribers and is known as a coupling and a loose coupling, [0032]), the transmission server and the reception server separate from the one or more processors, wherein the transmission server corresponds to a first data store or interface of an enterprise management system, and the reception server corresponds to a second data store or interface of the enterprise management system (controlling and monitoring of an individual complex enterprise process that crosses different IT (Information Technology) systems (business applications and services), connected and disconnected, inside and outside of an enterprise, including collaborative activities, human driven or unstructured processes, throughout Internet and non-structured data sources, based on a method of process-instance identification from extracted message-instance content, [0019]. Receiving messages exchanged between the plurality of workstations or/and computerized services and having content, and for deriving from the content of the messages, monitoring information regarding the business process, [0067]);
extracting, by one or more processors, a signal corresponding to a first interaction with an entity from the message (Get two triad messages (in and out) as defined in the IT (Information Technology) system linked to the given triad, and find the data fields that are available both in each of the messages and in the Meta-tag Spec, [0355]. An example of connecting triads is as follows: Consider the following triads: a. sent purchase order--->supplier--->invoice | c. sent purchase order--->supplier--->shipping receipt, [0360]-[0362]);
determining, by the one or more processors, an indication of an entity identity based on the signal (a data-centric process monitoring system, in accordance with an embodiment of the present invention, is provided. A set of triads such as <Incoming message, Entity, Outgoing message> typically constitute building blocks of this embodiment of the invention, [0029]. The meta-tag is generated. It may be applied on each triad's messages including those that divide the triad into two or more triads. Meta-tag Spec is the file that comprises all possible data field names enabling an identity for a specific customer, supplier, or employee at different steps of process execution, [0355]).
Webster then additionally or alternatively discloses:
extracting, by one or more processors, a signal corresponding to a first interaction with an entity (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]);
determining, by the one or more processors, an indication of an entity identity based on the signal (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]);
receiving, by the one or more processors, a query associated with the entity, based on the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18], [Column 8, Line 34 – Column 9, Line 6]);
generating, by the one or more processors and responsive to the query, interaction basis information, the interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]); and
presenting, by the one or more processors, the interaction basis information via a user interface (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]).
It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Shapira for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users.
Regarding claim 2, Webster further discloses:
storing, by the one or more processors, a first data record corresponding to the signal, the first data record comprising the entity identity and an indication of a first communications channel for the first interaction (A user's preferred channel of communication may be identified via his or her preferences. In one example, a user may initiate a first medium of communication, via a text message, smartphone application, call, etc. As a result, the user call processing system may identify the inquiry from the user and apply one or more preferences to the result, [Column 10, Lines 7-17]);
determining, by the one or more processors, a second communications channel associated with the query, the second communications channel different from the first communications channel (phone calls which are dialed out of a user device a one option among many options to contact a customer support service center. In another example embodiment, the user may be accessing customer support via any communication channel/medium, such as email, live chat applications, website access, and mobile device applications. For example, transmitting menu options and/or automatically selecting a menu option for a user may be performed responsive to identifying the user and one or more of his or her preferences for processing customer support inquiries, [Column 9, Line 61 – Column 10, Line 6]); and
retrieving, by the one or more processors, the first data record based on the entity identity, wherein the generation of the interaction basis information is based on the first communications channel and the second communications channel (retrieving a user profile from memory that includes the history information based on previous interactions between the user device and the customer call center server (e.g., calls, messages, spoken dialogue, account information, etc.), [Column 10, Lines 44-55]. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]).
Regarding claim 3, Webster further discloses intercepting a message conveyed between a transmission server and a reception server, the transmission server and the reception server separate from the one or more processors; and storing the signal comprises: storing the message; and storing an indication of the transmission server or the reception server (A user's preferred channel of communication may be identified via his or her preferences. In one example, a user may initiate a first medium of communication, via a text message, smartphone application, call, etc. As a result, the user call processing system may identify the inquiry from the user and apply one or more preferences to the result. In one example, the user may text an inquiry for an upgrade in service and receive an email with information regarding the upgrade since that is the user's preference to communicate with email, [Column 10, Lines 7-17]).
Regarding claim 4, Webster further discloses the signal is one signal of a plurality of signals, each of the plurality of signals corresponding to a different interaction with the entity (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc., [Column 8, Line 34 – Column 9, Line 6]), and comprising:
retrieving, by the one or more processors, the plurality of signals associated with the entity (Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]);
prioritizing, by the one or more processors, the plurality of signals based on the query (The algorithm of the likelihood function would then likely extract a main preference to be [politics] and a secondary preference to be [sports] based on the various information submitted from the user account. Those preferences then can be queued in order depending on their relevance. The relevance may be based on an assigned weight value proportional to the number of times the words appear for that category, [Column 8, Line 34 – Column 9, Line 6]); and
presenting, by the one or more processors, the interaction basis information based on the prioritization (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]).
Regarding claim 5, Webster further discloses:
matching, by the one or more processors, the entity identity to a field of a machine-readable record generated based on an entity action, to contextualize a human-readable record (the user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile, [Column 6, Lines 19-56]);
parsing, by the one or more processors, the human-readable record to determine a content of the first interaction (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258, [Column 9, Lines 19-56]); and
generating, by the one or more processors, the interaction basis information based on the content of the first interaction (During the user history identification procedure, the inquiry/call purpose may be identified via a predictive analysis that applied the likelihood function to a prediction operation that labels the user's inquiry as being associated with a particular purpose 260. The next determination may be to determine whether the inquiry message or call should be responded to with a promotional advertisement or whether the user needs immediate support 262. If the call requires support from a technical perspective or other service oriented issue, the call may be automatically forwarded to a call center agent in the corresponding department 264 that can respond with an automated all service, an automated text message service or even a live agent service, [Column 6, Line 57 – Column 7, Line 7], [Column 8, Line 34 – Column 9, Line 6]).
Regarding claim 7, Webster further discloses the interaction basis information comprises historical records of the first interaction (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc. Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information, [Column 8, Line 34 – Column 9, Line 6]) and a plurality of further interactions with the entity (if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]).
Regarding claim 8, Webster further discloses routing, by the one or more processors, a communication channel associated with a second entity interaction to a resource based on the interaction basis information (the user may be accessing customer support via any communication channel/medium, such as email, live chat applications, website access, and mobile device applications. For example, transmitting menu options and/or automatically selecting a menu option for a user may be performed responsive to identifying the user and one or more of his or her preferences for processing customer support inquiries, or perhaps bypassing a menu and providing direct access to an automated customer support dialogue operation of the customer service processing system, [Column 9, Line 61 – [Column 10, Line 6]).
Regarding claim 9, Webster further discloses the query includes an indication of an interaction basis (The users that may have elected to have billing information as their top priority will be identified according to a confirmed menu option choice that is stored in the user's profile information. The profile information will be retrieved based on the identified user information and used as a flag or identifier by the call processing system as a trigger to provide an automated ‘present balance due’ parameter to the user without delay, [Column 3, Lines 24-49]).
Regarding claim 10, Webster further discloses the interaction basis information comprises a prediction of an interaction basis, based on the historical records (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject and identify the user's preferences accordingly, [Column 6, Lines 19-56], [Column 8, Line 34 – Column 9, Line 6]).
Regarding claim 12, Webster further discloses:
the first interaction with the entity comprises a first electronic communication (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]);
the indication of the entity identity comprises a telephone number associated with the first electronic communication (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]);
the query is generated responsive to a telephonic communication associated with the telephone number, the query generated during the telephonic communication (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18]);
the interaction basis information is based on a data record generated based on the signal (The user history may be retrieved 254, [Column 6, Lines 4-18]. The user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258, [Column 6, Lines 19-56]); and
the interaction basis information is presented to a display for a client support agent receiving the telephonic communication (The user history may be retrieved 254 and forwarded 256 to the customer support server 244, [Column 6, Lines 4-18]).
Regarding claim 13, Shapira clearly shows and discloses a non-transitory computer-readable medium having machine instructions stored thereon, the instructions being executable by a processor to cause the processor to perform operations (Figure 4) comprising:
intercepting a message conveyed between a transmission server and a reception server (Message brokers may be software applications that implement Publish and Subscribe mechanisms as an effective way of disseminating information to multiple users. Business applications and services connected to a particular message broker are typically written so that a “community” of clients with a common purpose enables them to send and receive messages among themselves. A message broker may be an intermediary acting between publishers and subscribers and is known as a coupling and a loose coupling, [0032]), the transmission server and the reception server separate from the processor (controlling and monitoring of an individual complex enterprise process that crosses different IT (Information Technology) systems (business applications and services), connected and disconnected, inside and outside of an enterprise, including collaborative activities, human driven or unstructured processes, throughout Internet and non-structured data sources, based on a method of process-instance identification from extracted message-instance content, [0019]. Receiving messages exchanged between the plurality of workstations or/and computerized services and having content, and for deriving from the content of the messages, monitoring information regarding the business process, [0067]);
extracting a signal corresponding to a first interaction with an entity from the message (Get two triad messages (in and out) as defined in the IT (Information Technology) system linked to the given triad, and find the data fields that are available both in each of the messages and in the Meta-tag Spec, [0355]. An example of connecting triads is as follows: Consider the following triads: a. sent purchase order--->supplier--->invoice | c. sent purchase order--->supplier--->shipping receipt, [0360]-[0362]);
determining an indication of an entity identity based on the signal (a data-centric process monitoring system, in accordance with an embodiment of the present invention, is provided. A set of triads such as <Incoming message, Entity, Outgoing message> typically constitute building blocks of this embodiment of the invention, [0029]. The meta-tag is generated. It may be applied on each triad's messages including those that divide the triad into two or more triads. Meta-tag Spec is the file that comprises all possible data field names enabling an identity for a specific customer, supplier, or employee at different steps of process execution, [0355]).
Webster then additionally or alternatively discloses:
extracting a signal corresponding to a first interaction with an entity (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]);
determining an entity identity based on the signal (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]);
receiving a query associated with the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18]);
generating, responsive to the query, interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]);
prioritizing the interaction basis information for display (The algorithm of the likelihood function would then likely extract a main preference to be [politics] and a secondary preference to be [sports] based on the various information submitted from the user account. Those preferences then can be queued in order depending on their relevance. The relevance may be based on an assigned weight value proportional to the number of times the words appear for that category, [Column 8, Line 34 – Column 9, Line 6]); and
presenting prioritized interaction basis information via a user interface (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]).
It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Shapira for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users.
Regarding claim 14, Webster further discloses storing a data record corresponding to a message, the data record comprising the entity identity (the user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile, [Column 8, Line 34 – Column 9, Line 6]), wherein extracting the signal comprises establishing a connector with a monitoring port, the connector configured to intercept the message (when the user device transmits an inquiry message to the customer support system 115, the user's social networking information (when the user device transmits an inquiry message to the customer support system 115, the user's social networking information e.g., FACEBOOK®, TWITTER®, LINKEDIN®, etc.), and the information may be parsed to identify terms that match a predefined list of terms used to identify and create preferences associated with the user. For example, if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]).
Regarding claim 15, Webster further discloses the interaction basis information is based on: the first interaction (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc. Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information, [Column 8, Line 34 – Column 9, Line 6]); and a plurality of further interactions with the entity (if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]).
Regarding claim 16, Webster further discloses the prioritization is based on:
a recency of one or more data records of the interaction basis information (the politics related terms “gun control”, “Obama”, “Congress”, etc., may appear four times in the user's personal stored information and the terms “LA Lakers” and “NFL” are two instances of sports terms, and may be required to appear over a recent window of time, such as 10, 20, 30, 60 days, [Column 8, Line 34 – Column 9, Line 6]);
a communications channel for the one or more data records of the interaction basis information (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]); and
a content of the one or more data records of the interaction basis information (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc, [Column 8, Line 34 – Column 9, Line 6]).
Regarding claim 17, Webster further discloses routing an electronic communication to a client support agent based on the interaction basis information (if a user is a platinum customer, the application would look at agent availability and transfer the user directly to an agent if one is available or provide the user with their favorite menu choices, [Column 10, Lines 28-43]).
Regarding claim 18, Webster further discloses the query includes an indication of an interaction basis (The users that may have elected to have billing information as their top priority will be identified according to a confirmed menu option choice that is stored in the user's profile information. The profile information will be retrieved based on the identified user information and used as a flag or identifier by the call processing system as a trigger to provide an automated ‘present balance due’ parameter to the user without delay, [Column 3, Lines 24-49]).
Regarding claim 20, Shapira clearly shows and discloses a first server (Figure 4) configured to:
intercept a message conveyed between a transmission server and a reception server (Message brokers may be software applications that implement Publish and Subscribe mechanisms as an effective way of disseminating information to multiple users. Business applications and services connected to a particular message broker are typically written so that a “community” of clients with a common purpose enables them to send and receive messages among themselves. A message broker may be an intermediary acting between publishers and subscribers and is known as a coupling and a loose coupling, [0032]), the transmission server and the reception server separate from the first server, the transmission server and the reception server separate from the one or more processors, wherein the transmission server corresponds to a first data store or interface of an enterprise management system, and the reception server corresponds to a second data store or interface of the enterprise management system (controlling and monitoring of an individual complex enterprise process that crosses different IT (Information Technology) systems (business applications and services), connected and disconnected, inside and outside of an enterprise, including collaborative activities, human driven or unstructured processes, throughout Internet and non-structured data sources, based on a method of process-instance identification from extracted message-instance content, [0019]. Receiving messages exchanged between the plurality of workstations or/and computerized services and having content, and for deriving from the content of the messages, monitoring information regarding the business process, [0067]);
extract from a plurality of connectors corresponding to a plurality of data sources, a first plurality of signals corresponding to one or more first entity interactions from the message (Get two triad messages (in and out) as defined in the IT (Information Technology) system linked to the given triad, and find the data fields that are available both in each of the messages and in the Meta-tag Spec, [0355]. An example of connecting triads is as follows: Consider the following triads: a. sent purchase order--->supplier--->invoice | c. sent purchase order--->supplier--->shipping receipt, [0360]-[0362]);
determine, based on one or more of the first plurality of signals, an indication of an entity identity (a data-centric process monitoring system, in accordance with an embodiment of the present invention, is provided. A set of triads such as <Incoming message, Entity, Outgoing message> typically constitute building blocks of this embodiment of the invention, [0029]. The meta-tag is generated. It may be applied on each triad's messages including those that divide the triad into two or more triads. Meta-tag Spec is the file that comprises all possible data field names enabling an identity for a specific customer, supplier, or employee at different steps of process execution, [0355]).
Webster then additionally or alternatively discloses:
extract, from a plurality of connectors corresponding to a plurality of data sources, a first plurality of signals corresponding to one or more first entity interactions (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]);
determine, based on one or more of the first plurality of signals, an indication of an entity identity (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]);
receive a query associated with the entity, a data field of the query corresponding to the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18], [Column 8, Line 34 – Column 9, Line 6]);
generate, responsive to the query, interaction basis information for presentation, the interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]); and
present the interaction basis information (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]).
It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Shapira for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users.
Claims 6, 11, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Shapira in view of Webster and further in view of Hartman et al. (Pub. No. US 2020/0045178, published on February 6, 2020; hereinafter Hartman).
Regarding claim 6, Webster further discloses determining, by the one or more processors, an account type based on the indication of the entity identity, wherein the plurality of signals is prioritized based on the account type (if a user is a platinum customer, the application would look at agent availability and transfer the user directly to an agent if one is available or provide the user with their favorite menu choices, [Column 10, Lines 28-43]).
Hartman then discloses the indication of the entity identity is an account number for one account type of a plurality of account types (the external entities 180A-180N may include businesses and other organizations that seek to offer phone-based service or support to their customers (or potential customers) through IVR processes. As another example, the external entities 180A-180N may include individual merchants who offer goods and/or services through a common electronic marketplace that is open to many such merchants, [0022]. The user metadata may include a user's full name, a user's street address, a user's e-mail address, a user's phone number for contacting or being contacted by entities 180A-180N, [0047]).
It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Hartman with the teachings of Shapira, as modified by Webster, for the purpose of utilizing known data associated an entity to provide user-friendly support and enable interactive response associated with a request from the entity based at least one the entity’s identity and preferences.
Regarding claims 11, and 19, Hartman further discloses:
the entity comprises a plurality of sub-entities, each sub-entity associated with a unique identifier (the device-specific accounts may be assigned to another “umbrella” account or a pool of accounts, such as a corporate account associated with an organizational customer of the service provider environment, e.g., for ease of device management, [0047]); and
the interaction basis information is based on a first unique identifier associated with the first interaction (the request 131 may include suitable information associated with the entity 180A, such as a phone number at which the entity can be contacted, a name of the entity, an Internet domain name of the entity, and so on, [0025]. The order history may be retrieved from a component of the service provider environment or from a component of the external entity 180A, e.g., a data store associated with that entity, [0031]), and a second unique identifier associated with the query (In response to the request 131, the IVR registration component 130 may generate a certificate 132 that is specific to the entity 180A. The IVR registration component 130 may send the certificate 132 to the computing device 185A or to any other address or storage location at which the entity 180A expects to receive the certificate. The IVR registration component 130 may also store a copy of the certificate 132, e.g., in order to compare the stored copy with a copy retrieved from the entity 180A in the future, [0026]).
Relevant Prior Art
The following references are considered relevant to the claims:
Yasnoff (Pat. No. US 11477144) teaches receiving a message having lead information, initiating a conversation with a prospect identified in the lead information, and sending a modified version of the message to a CRM system, wherein the modified version of the message includes information about the conversation. The information about the conversation may include a hyperlink to the conversation in a messaging platform. The prospect identified is assigned in the lead information to a representative. The modified version of the message may identify the representative. Conversation may include a message to the prospect identified in the lead information. The message to the prospect may be automatically personalized to the prospect. The message having lead information may be intercepted between a lead source and a CRM system.
McGrath et al. (Pub. No. US 2023/0077995) teaches an automation framework system may include a service portal, an API gateway, an entitlements microservice, and a resources microservice. The service portal is configured to provide access to automation functionality of the automation framework system. The service portal is configured to provide entitlement models for generating a programming interface API or automation. The API gateway is configured to intercept API requests from a client device. The API gateway is configured to grant or reject the API requests based on each requested API and information about a user the client device. The entitlements microservice is configured to determine whether the user of the client device is permitted to access the API based on group information associated with the client device.
Contact Information
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Son T. Hoang whose telephone number is (571) 270-1752. The Examiner can normally be reached on Monday – Friday (7:00 AM – 4:00 PM).
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Sherief Badawi can be reached on (571) 272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SON T HOANG/Primary Examiner, Art Unit 2169 July 25, 2026
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