DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/05/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
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 –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sohum et al. (Sohum), US Patent Application Publication No. US 2021/0117893 A1.
As to independent claim 1, Sohum discloses a device for coordinating resources in multiplatform environments, the device (Figure 3, paragraphs [0047]: an interactive computing environment for switching and handover between the one or more intelligent conversational agents includes one or more communication device) comprising:
a processor (paragraph [0012]: computing device includes one or more processor);
a communications module coupled to the processor (Figures 3, 6, paragraphs [0047], [0121]: communication network is connected with the one or more communication devices (processor); and
a memory coupled to the processor, the memory storing computer executable
instructions that when executed by the processor cause the processor to (paragraph [0012]: the memory is coupled to the one or more processor and the memory stores instructions, which are executed by the one or more processor)):
provide a first platform to receive a first query, the first query for determining one or more properties of a process of a second platform of an enterprise (paragraphs [0012] and [0056]: a user connects with the interactive computing environment through a communication device D1, i.e., a smartphone (a first platform) to access a mega bot M1 (intermediary platform), and the user sends a query for a mega bot at the chatbot switching system (second platform), wherein the query has a plurality of aspects (properties), which includes context, linguistic style, sentence construction (properties));
select a machine learning model from a plurality of machine learning models based on the first query, the selected machine learning model being associated with the second platform that interfaces with the process (paragraphs [0012] and [0064]: performing to enable selection of a suitable intelligent conversational agent (a machine learning model) from the one or more intelligent conversational agents, wherein the selection the suitable intelligent conversational agent from the one or more intelligent conversational agents having the trust score above the threshold level according to the plurality of aspect (properties) of the query);
generate a second query, based on the first query, for the selected machine learning model (paragraph [0068]: the chatbot switching system (the second platform) creates a response (a second query) for the query at the mega bot using the suitable intelligent conversational agent from the one or more intelligent conversational agents);
use the second query and the selected machine learning model to search the second platform to determine properties of the process and output one or more determined properties, the selected machine learning model having been trained based on queries from intermediary platforms (paragraphs [0060], [0068]: the mega bot (intermediary platform) provides response (second query) to the user, the mega bot respond to the one or more queries of the plurality of users based on selection and switching of the one or more intelligent conversational agents); and
serve, via the first platform, the one or more determined properties as a response to the first query (paragraphs [0060], [0068], [0075]: the mega bot provides response to the user of the device; Also see paragraphs [0082]-[0085] for different queries, different responses according to the different queries, and different selection of chatbots (machine learning models) according to the different queries).
As to dependent claim 2, Sohum discloses wherein the first query is provided by a user, and the intermediary platform is an automated platform for generating second queries from the user input first query (paragraphs [0075] and [0082]-[0085]).
As to dependent claim 3, Sohum discloses wherein each of a first group of machine learning models of the plurality of machine learning modes are trained to determine properties of different platforms (paragraphs [0065]-[0066]).
As to dependent claim 4, Sohum discloses wherein the second platform is an event handler that manages a plurality of processes for a plurality of platforms (paragraphs [0087], [0090]).
As to dependent claim 5, Sohum discloses wherein the selected machine learning model is trained to identify properties from the plurality of processes maintained by an event handler (paragraph [0066]).
As to dependent claim 6, Sohum discloses wherein the instructions cause the processor to retrain the selected machine learning model based on updating training data for the second platform (paragraph [0066]).
As to dependent claim 7, Sohum discloses wherein the instructions cause the processor to:
retrain another machine learning model of the plurality of machine learning models based on updating training data for another related platform (paragraph [0066]).
As to dependent claim 8, Sohum discloses wherein the first platform comprises a telephonic channel or a computer-based channel for receiving input from customers or employees (paragraph [0056]).
As to dependent claim 9, Sohum discloses wherein the computer-based channel is a chatbot (paragraph [0026]).
As to dependent claim 10, Sohum discloses wherein the selected machine learning model is trained with reference data representing workflows of the second platform (Abstract).
Claims 11-19 are method claims that contain similar limitations of claims 1-9, respectively. Therefore claims 11-19 are rejected under the same rationale.
Claim 20 is a computer readable medium claim that contains similar limitations of claim 1. Therefore, claim 20 is rejected under the same rationale.
Conclusion
Any inquiry concerning this communication should be directed to CHAU T NGUYEN at telephone number (571)272-4092. The examiner can normally be reached on M-F from 8am to 5pm (PT).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cesar Paula, can be reached at telephone number 5712724128. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHAU T NGUYEN/Primary Examiner, Art Unit 2145