DETAILED ACTION
1. This office action is in response to application 19/286,458 filed on 7/31/2025. Claims 1-20 are pending in this office action.
Notice of Pre-AIA or AIA Status
2. 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
3. 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.
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Claims 1-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4 and 12 of U.S. Patent No. 12,406,234 in view of US 2020/0293564 (hereinafter Reh). Although the claims at issue are not identical, they are not patentably distinct from each other because the limitations in bold are the same and the differences would have been obvious to an artisan of ordinary skill in the art. With respect to claims 1-4 an artisan of ordinary skill in the art understands that data that is created or defined is associated with previous data within the system and that the created or defined data must be maintained.
With respect to claim 5 Reh renders obvious generating, by a machine learning system, the occurrence of the event instance as a machine learning task executed by the machine learning system (See paragraphs 0024, 0048 note the machine learning system is responsible for task and optimization). It would have been obvious to an artisan of ordinary skill in the pertinent at the time the instantly claimed invention was filed to have incorporated the teaching of Reh into the system of US 12,406,234. The modification would have been obvious because the two references are concerned with the solution to problem of customer relations management (See US 12, 406, 234 abstract and Reh paragraph 0023), therefore there is an implicit motivation to combine these references (i.e. motivation from the references themselves). In other words, the ordinary skilled artisan, during his/her quest for a solution to the cited problem, would look to the cited references at the time the invention was made. Consequently, the ordinary skilled artisan would have been motivated to combine the cited references since Reh’s teaching would enable users of the US 12,406,234 system to have more efficient processing of CRM data.
With respect to claim 6 Reh renders obvious; training, by a machine learning system, an event classification model for identifying events (See paragraphs 0044, 0048 and 0066-0068 note the training is used for the ontology to classify data as events). It would have been obvious to an artisan of ordinary skill in the pertinent at the time the instantly claimed invention was filed to have incorporated the teaching of Reh into the system of US 12,406,234. The modification would have been obvious because the two references are concerned with the solution to problem of customer relations management (See US 12, 406, 234 abstract and Reh paragraph 0023), therefore there is an implicit motivation to combine these references (i.e. motivation from the references themselves). In other words, the ordinary skilled artisan, during his/her quest for a solution to the cited problem, would look to the cited references at the time the invention was made. Consequently, the ordinary skilled artisan would have been motivated to combine the cited references since Reh’s teaching would enable users of the US 12,406,234 system to have more efficient processing of CRM data.
With respect to claim 7 Reh renders obvious; training, by a machine learning system, an event classification model for identifying an event as an indicator that a change is to be implemented to address a changing need (See paragraphs 0044, 0048 and 0066-0068 note the training is used for the ontology to classify data as events). It would have been obvious to an artisan of ordinary skill in the pertinent at the time the instantly claimed invention was filed to have incorporated the teaching of Reh into the system of US 12,406,234. The modification would have been obvious because the two references are concerned with the solution to problem of customer relations management (See US 12, 406, 234 abstract and Reh paragraph 0023), therefore there is an implicit motivation to combine these references (i.e. motivation from the references themselves). In other words, the ordinary skilled artisan, during his/her quest for a solution to the cited problem, would look to the cited references at the time the invention was made. Consequently, the ordinary skilled artisan would have been motivated to combine the cited references since Reh’s teaching would enable users of the US 12,406,234 system to have more efficient processing of CRM data.
With respect to claim 8 Reh renders obvious; generating, by a conversation intelligence system, an event based on a conversation or call (See paragraphs 0035, note call logs, chat logs, bot logs etc.). It would have been obvious to an artisan of ordinary skill in the pertinent at the time the instantly claimed invention was filed to have incorporated the teaching of Reh into the system of US 12,406,234. The modification would have been obvious because the two references are concerned with the solution to problem of customer relations management (See US 12, 406, 234 abstract and Reh paragraph 0023), therefore there is an implicit motivation to combine these references (i.e. motivation from the references themselves). In other words, the ordinary skilled artisan, during his/her quest for a solution to the cited problem, would look to the cited references at the time the invention was made. Consequently, the ordinary skilled artisan would have been motivated to combine the cited references since Reh’s teaching would enable users of the US 12,406,234 system to have more efficient processing of CRM data.
19/286,458 12406234
1. A computer-implemented method, comprising: constructing a custom event record for a custom object within a customer relationship management (CRM) system according to an event type definition; configuring the custom event record to track an event type defined by the event type definition; monitoring for an occurrence of an event instance of the event type; and in response to detecting an occurrence of the event instance of the event type tracked by the custom event record, associating the event instance with an event log of the custom event record.
1. A method, comprising: receiving a selection of a custom object within a customer relationship management (CRM) system; receiving a definition of an event type definition for the custom object; storing an ontology that defines a set of objects and respective associations between the set of objects, wherein the set of objects includes the custom object; wherein the ontology is a client-specific ontology of a client of a multi-service platform that includes custom objects that are specific to the client; constructing a custom event record for the custom object; configuring the custom event record to track an event type defined by the event type definition; monitoring for an occurrence of an event instance of the event type; and in response to an occurrence of the event instance associating the event instance with an event log of the custom event record.
2. The computer-implemented method of claim 1, comprising: defining the event type definition specifying a set of event types to track with respect to an instance of the custom object and a set of event properties.
4. The method of claim 1, comprising: receiving a user selection of the custom object and the event type definition to associate with the custom event record, wherein the event type definition indicates a set of event types tracked with respect to an instance of the custom object and a set of event properties.
3. The computer-implemented method of claim 1, comprising: defining the event type definition specifying a set of event types to track with respect to an instance of the custom object and a set of event properties.
12. The computing system of claim 9, wherein the operations comprise: receiving a user selection of the custom object and the event type definition to associate with the custom event record, wherein the event type definition indicates a set of event types tracked with respect to an instance of the custom object and a set of event properties.
4. The computer-implemented method of claim 1, comprising: maintaining the event log to track a time-sequenced log of event instances recorded for the custom object.
2. The method of claim 1, comprising: creating the event log to provide a time-sequenced log of event instances recorded for the custom object.
Claims 9-16 are system claims substantially corresponding to the method of claims 1-8 and are thus rejected for the same reasons as set forth in the rejection of claims 1-18.
Claims 17-20 are non-transitory computer readable medium claims substantially corresponding to the method of claims 1, 7, 8 and 2 and are thus rejected for the same reasons as set forth in the rejection of claims 1, 7, 8, and 2.
Claim Rejections - 35 USC § 102
4. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Reh.
As for claim 1 Reh discloses: A computer-implemented method, comprising: constructing a custom event record for a custom object within a customer relationship management (CRM) system according to an event type definition (See paragraph 0023 note the domain includes an enterprise resource planning application and a customer relationship management system); configuring the custom event record to track an event type defined by the event type definition (See paragraphs 0024 and 0046 note the system will define events according to a user defined semantics); monitoring for an occurrence of an event instance of the event type (See paragraphs 0025, 0026 and 0038 note the system monitors transactions for the user defined events); and in response to detecting an occurrence of the event instance of the event type tracked by the custom event record, associating the event instance with an event log of the custom event record (See paragraph 0035 note the system will associated targeted data will logs, call logs, chat logs, bot logs, etc).
As for claim 2 the rejection of claim 1 is incorporated and further Reh discloses; defining the event type definition specifying a set of event types to track with respect to an instance of the custom object and a set of event properties (See paragraphs 0045, 0052 and 0077 note attributes are properties and mapped to values).
As for claim 3 the rejection of claim 1 is incorporated and further Reh discloses; defining the event type definition specifying a set of event types to track with respect to an instance of the custom object and a set of event properties (See paragraph 0022 and 0041 note the entities are specified than track and confirm certain events like purchases).
As for claim 4 the rejection of claim 1 is incorporated and further Reh discloses: maintaining the event log to track a time-sequenced log of event instances recorded for the custom object (See paragraphs 0024, 0038 and 0041 note the system will structure logs based on metrics such as time, cost etc. along a timeline).
As for claim 5 the rejection of claim 1 is incorporated and further Reh discloses; generating, by a machine learning system, the occurrence of the event instance as a machine learning task executed by the machine learning system (See paragraphs 0024, 0048 note the machine learning system is responsible for task and optimization).
As for claim 6 the rejection of claim 1 is incorporated and further Reh discloses; training, by a machine learning system, an event classification model for identifying events (See paragraphs 0044, 0048 and 0066-0068 note the training is used for the ontology to classify data as events).
As for claim 7 the rejection of claim 1 is incorporated and further Reh discloses; training, by a machine learning system, an event classification model for identifying an event as an indicator that a change is to be implemented to address a changing need (See paragraphs 0044, 0048 and 0066-0068 note the training is used for the ontology to classify data as events).
As for claim 8 the rejection of claim 1 is incorporated and further Reh discloses; generating, by a conversation intelligence system, an event based on a conversation or call (See paragraphs 0035, note call logs, chat logs, bot logs etc).
Claims 9-16 are system claims substantially corresponding to the method of claims 1-8 and are thus rejected for the same reasons as set forth in the rejection of claims 1-18.
Claims 17-20 are non-transitory computer readable medium claims substantially corresponding to the method of claims 1, 7, 8 and 2 and are thus rejected for the same reasons as set forth in the rejection of claims 1, 7, 8, and 2.
Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELIYAH STONE HARPER whose telephone number is (571)272-0759. The examiner can normally be reached on Monday-Friday 10:00 am - 6:00 pm.
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/Eliyah S. Harper/Primary Examiner, Art Unit 2166 June 10, 2026
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