IP Library Granted Patent US 12,380,390
Granted Patent B2
US 12,380,390 · App. 17/405,312 · Granted Aug 5, 2025

Change management system and method

Inventor: Kevin Carr (Milford, CT)
Assignee: EDERA L3C
G06Q10/0637G06F40/30G06Q10/06313G06Q10/06315G06Q10/06316G06Q10/0635G06Q10/06375G06Q10/105H04L51/02
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,380,390
App. No.
17/405,312
Granted
Aug 5, 2025
Kind
B2
Abstract

A method, computer program product, and computing system for gathering transition information from a user concerning a business process transition event; and processing the transition information to generate a bespoke journey concerning the business process transition event.

Claims (99)

1. A computer-implemented method, executed on a computing device, comprising:

gathering transition information from a user concerning a business process transition event, wherein the business process transition event includes a business process transition event from a first business process to a second business process;

processing the transition information to generate a plurality of bespoke journeys concerning the business process transition event relative to a plurality of recipients based upon, at least in part, each respective recipient's role and one or more functionalities associated with the second business process, wherein generating each bespoke journey includes populating the bespoke journey with a plurality of subevents selected to guide the plurality of recipients through the business process transition event from the first business process to the second business process for the respective recipient's role, and wherein the plurality of subevents include one or more training subevents selected to train the respective recipient with the functionalities associated with the second business process that concern the respective recipient's role;

providing the plurality of bespoke journeys concerning the business process transition event to each of the plurality of recipients, wherein each bespoke journey includes one or more subevents configured to guide the respective recipient through the business process transition event for their role and the one or more functionalities associated with the second business process, wherein providing the plurality of bespoke journeys concerning the business process transition event includes:

populating a user interface associated with a respective recipient with the plurality of subevents associated with the respective recipient's role and the one or more functionalities associated with the second business process,

receiving one or more selections of subevents to access within the user interface; and

prompting the respective recipient in real-time to complete the plurality of subevents associated with the respective recipient using a virtual bot; wherein prompting the respective recipient using the virtual bot includes:

gathering information concerning the plurality of subevents associated with the respective recipient using the virtual bot, wherein gathering information from the plurality of subevents includes iteratively prompting the respective recipient with the virtual bot via the user interface until the virtual bot determines that no further information is needed;

performing sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient using the virtual bot to gauge sentiment concerning a particular subevent by performing sentiment analysis on the information gathered from the respective recipient concerning the particular subevent using a machine learning model to define a sentiment metric for the particular subevent, wherein the machine learning model extracts one or more key words from the information gathered from the respective recipient and flags the one or more key words as: positive, negative, or neutral;

in response to defining a negative sentiment metric for the particular subevent, adapting subsequent prompting of the respective recipient using the virtual bot based upon, at least in part, the sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient, wherein the virtual bot provides one or more follow up questions to the respective recipient; and

in response to defining the negative sentiment metric for the particular subevent, modifying content of a subevent of the plurality of subevents within the bespoke journey that is provided to at least the respective recipient as part of the bespoke journey based upon, at least in part, the negative sentiment metric for the particular subevent.

2. The computer-implemented method of claim 1 wherein the first business process includes one or more of:

a first operating platform;

a first software platform;

a first hardware platform;

a first operating environment; and

a first operational system.

3. The computer-implemented method of claim 1 wherein the second business process includes one or more of:

a second operating platform;

a second software platform;

a second hardware platform;

a second operating environment; and

a second operational system.

4. The computer-implemented method of claim 1 wherein the business process transition event concerns a transition event from a first business operational process to a second operational process.

5. The computer-implemented method of claim 1 wherein gathering transition information from a user concerning a business process transition event includes:

rendering a user interface that is configured to gather transition information from the user concerning the business process transition event.

6. The computer-implemented method of claim 1 further comprising:

defining a plurality of journey scenarios;

presenting the plurality of journey scenarios to the user for review; and

enabling the user to select a specific journey scenario from the plurality of joumey scenarios for the business process transition event.

7. The computer-implemented method of claim 6 wherein processing the transition information to generate a bespoke journey concerning the business process transition event includes:

processing the specific journey scenario and the transition information to generate the bespoke journey concerning the business process transition event.

8. The computer-implemented method of claim 1 wherein processing the transition information to generate a bespoke journey concerning the business process transition event includes:

providing, via a user interface, a listing of subevents for the business process transition event based upon, at least in part, one or more of: the user's role and one or more functionalities associated with the second business process; and

receiving, via the user interface, a selection of one or more subevents from the listing of subevents for inclusion in the bespoke journey, wherein receiving the selection of the one or more subevents from the listing of subevents for inclusion in the bespoke journey includes providing the selection of the one or more subevents in a graphical representation of the bespoke journey including sequencing of subevents relative to one another.

9. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

gathering transition information from a user concerning a business process transition event, wherein the business process transition event includes a business process transition event from a first business process to a second business process;

processing the transition information to generate a plurality of bespoke journeys concerning the business process transition event relative to a plurality of recipients based upon, at least in part, each respective recipient's role and one or more functionalities associated with the second business process, wherein generating each bespoke journey includes populating the bespoke journey with a plurality of subevents selected to guide the plurality of recipients through the business process transition event from the first business process to the second business process for the respective recipient's role, and wherein the plurality of subevents include one or more training subevents selected to train the respective recipient with the functionalities associated with the second business process that concern the respective recipient's role;

providing the plurality of bespoke journeys concerning the business process transition event to each of the plurality of recipients, wherein each bespoke journey includes one or more subevents configured to guide the respective recipient through the business process transition event for their role and the one or more functionalities associated with the second business process, wherein providing the plurality of bespoke journeys concerning the business process transition event includes:

populating a user interface associated with a respective recipient with the plurality of subevents associated with the respective recipient's role and the one or more functionalities associated with the second business process,

receiving one or more selections of subevents to access within the user interface; and

prompting the respective recipient in real-time to complete the plurality of subevents associated with the respective recipient using a virtual bot; wherein prompting the respective recipient using the virtual bot includes:

gathering information concerning the plurality of subevents associated with the respective recipient using the virtual bot, wherein gathering information from the plurality of subevents includes iteratively prompting the respective recipient with the virtual bot via the user interface until the virtual bot determines that no further information is needed;

performing sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient using the virtual bot to gauge sentiment concerning a particular subevent by performing sentiment analysis on the information gathered from the respective recipient concerning the particular subevent using a machine learning model to define a sentiment metric for the particular subevent, wherein the machine learning model extracts one or more key words from the information gathered from the respective recipient and flags the one or more key words as: positive, negative, or neutral;

in response to defining a negative sentiment metric for the particular subevent, adapting subsequent prompting of the respective recipient using the virtual bot based upon, at least in part, the sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient, wherein the virtual bot provides one or more follow up questions to the respective recipient; and

in response to defining the negative sentiment metric for the particular subevent, modifying content of a subevent of the plurality of subevents within the bespoke journey that is provided to at least the respective recipient as part of the bespoke journey based upon, at least in part, the negative sentiment metric for the particular subevent.

10. The computer program product of claim 9 wherein the first business process includes one or more of:

a first operating platform;

a first software platform;

a first hardware platform;

a first operating environment; and

a first operational system.

11. The computer program product of claim 9 wherein the second business process includes one or more of:

a second operating platform;

a second software platform;

a second hardware platform;

a second operating environment; and

a second operational system.

12. The computer program product of claim 9 wherein the business process transition event concerns a transition event from a first business operational process to a second operational process.

13. The computer program product of claim 9 wherein gathering transition information from a user concerning a business process transition event includes:

rendering a user interface that is configured to gather transition information from the user concerning the business process transition event.

14. The computer program product of claim 9 further comprising:

defining a plurality of journey scenarios;

presenting the plurality of journey scenarios to the user for review; and

enabling the user to select a specific journey scenario from the plurality of joumey scenarios for the business process transition event.

15. The computer program product of claim 14 wherein processing the transition information to generate a bespoke journey concerning the business process transition event includes:

processing the specific journey scenario and the transition information to generate the bespoke journey concerning the business process transition event.

16. A computing system including a processor and memory configured to perform operations comprising:

gathering transition information from a user concerning a business process transition event, wherein the business process transition event includes a business process transition event from a first business process to a second business process;

processing the transition information to generate a plurality of bespoke journeys concerning the business process transition event relative to a plurality of recipients based upon, at least in part, each respective recipient's role and one or more functionalities associated with the second business process, wherein generating each bespoke journey includes populating the bespoke journey with a plurality of subevents selected to guide the plurality of recipients through the business process transition event from the first business process to the second business process for the respective recipient's role, and wherein the plurality of subevents include one or more training subevents selected to train the respective recipient with the functionalities associated with the second business process that concern the respective recipient's role;

providing the plurality of bespoke journeys concerning the business process transition event to each of the plurality of recipients, wherein each bespoke journey includes one or more subevents configured to guide the respective recipient through the business process transitionevent for their role and the one or more functionalities associated with the second business process, wherein providing the plurality of bespoke journeys concerning the business process transition event includes:

populating a user interface associated with a respective recipient with the plurality of subevents associated with the respective recipient's role and the one or more functionalities associated with the second business process,

receiving one or more selections of subevents to access within the user interface; and

prompting the respective recipient in real-time to complete the plurality of subevents associated with the respective recipient using a virtual bot; wherein prompting the respective recipient using the virtual bot includes:

gathering information concerning the plurality of subevents associated with the respective recipient using the virtual bot, wherein gathering information from the plurality of subevents includes iteratively prompting the respective recipient with the virtual bot via the user interface until the virtual bot determines that no further information is needed;

performing sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient using the virtual bot to gauge sentiment concerning a particular subevent by performing sentiment analysis on the information gathered from the respective recipient concerning the particular subevent using a machine learning model to define a sentiment metric for the particular subevent, wherein the machine learning model extracts one or more key words from the information gathered from the respective recipient and flags the one or more key words as: positive, negative, or neutral;

in response to defining a negative sentiment metric for the particular subevent, adapting subsequent prompting of the respective recipient using the virtual bot based upon, at least in part, the sentiment analysis on the information gathered concerning the plurality of subevents associated with the respective recipient, wherein the virtual bot provides one or more follow up questions to the respective recipient; and

in response to defining the negative sentiment metric for the particular subevent, modifying content of a subevent of the plurality of subevents within the bespoke journey that is provided to at least the respective recipient as part of the bespoke journey based upon, at least in part, the negative sentiment metric for the particular subevent.

17. The computing system of claim 16 wherein the first business process includes one or more of:

a first operating platform;

a first software platform;

a first hardware platform;

a first operating environment; and

a first operational system.

18. The computing system of claim 16 wherein the second business process includes one or more of:

a second operating platform;

a second software platform;

a second hardware platform;

a second operating environment; and

a second operational system.

19. The computing system of claim 16 wherein the business process transition event concerns a transition event from a first business operational process to a second operational process.

20. The computing system of claim 16 wherein gathering transition information from a user concerning a business process transition event includes:

rendering a user interface that is configured to gather transition information from the user concerning the business process transition event.

21. The computing system of claim 16 further comprising:

defining a plurality of journey scenarios;

presenting the plurality of journey scenarios to the user for review; and

enabling the user to select a specific journey scenario from the plurality of journey scenarios for the business process transition event.

22. The computing system of claim 21 wherein processing the transition information to generate a bespoke journey concerning the business process transition event includes:

processing the specific journey scenario and the transition information to generate the bespoke journey concerning the business process transition event.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 18, 2021
From: CARR, KEVIN
To: EDERA L3C
Reel/Frame 057213/0709 →
Continuity (2)
Provisional Application 63067108 · Aug 18, 2020
Related Publication 20220058544A1 · Feb 24, 2022
References Cited (144)
US 7574483B1 · Jang · 2009 [cited by applicant]
US 9565246B1 · Tsypliaev · 2017 [cited by applicant]
US 10129109B2 · Jayanti Venkata et al. · 2018 [cited by applicant]
US 10642936B2 · Arquero et al. · 2020 [cited by applicant]
US 10782984B2 · Schwartz et al. · 2020 [cited by applicant]
US 11055119B1 · Silverstein et al. · 2021 [cited by applicant]
US 11080914B2 · Lee et al. · 2021 [cited by applicant]
US 11388259B2 · Donohue · 2022 [cited by applicant]
US 11568148B1 · Nichols et al. · 2023 [cited by applicant]
US 20040059611A1 · Kananghinis · 2004 [cited by applicant]
US 20050033615A1 · Nguyen et al. · 2005 [cited by applicant]
US 20050097016A1 · Barnard · 2005 [cited by applicant]
US 20050114829A1 · Robin · 2005 [cited by applicant]
US 20050125249A1 · Takubo et al. · 2005 [cited by applicant]
US 20050187881A1 · McGiffin · 2005 [cited by applicant]
US 20060020500A1 · Turner · 2006 [cited by applicant]
US 20060026012A1 · Campbell · 2006 [cited by applicant]
US 20060242154A1 · Rawat · 2006 [cited by applicant]
US 20060259342A1 · Hartenstein · 2006 [cited by applicant]
US 20090043802A1 · Appel · 2009 [cited by applicant]
US 20100110933A1 · Wilcock · 2010 [cited by applicant]
US 20100150483A1 · Aida et al. · 2010 [cited by applicant]
US 20110307862A1 · Abrams · 2011 [cited by applicant]
US 20120047011A1 · Rippetoe · 2012 [cited by applicant]
US 20120072255A1 · Harthcryde et al. · 2012 [cited by applicant]
US 20120179512A1 · O'Keeffe · 2012 [cited by applicant]
US 20130080339A1 · Driesen et al. · 2013 [cited by applicant]
US 20130144678A1 · Ramachandran · 2013 [cited by applicant]
US 20140100922A1 · Aycock · 2014 [cited by applicant]
US 20140282227A1 · Nixon et al. · 2014 [cited by applicant]
US 20150161624A1 · Heath et al. · 2015 [cited by applicant]
US 20150332290A1 · Gerber · 2015 [cited by applicant]
US 20150348163A1 · Tamblyn et al. · 2015 [cited by applicant]
US 20160012368A1 · O'Connell et al. · 2016 [cited by applicant]
US 20160103856A1 · Isaacs · 2016 [cited by applicant]
US 20160243404A1 · Keller · 2016 [cited by applicant]
US 20160275458A1 · Meushar et al. · 2016 [cited by applicant]
US 20160300135A1 · Moudy et al. · 2016 [cited by applicant]
US 20160321583A1 · Jones et al. · 2016 [cited by applicant]
US 20160343004A1 · Brink · 2016 [cited by applicant]
US 20170039233A1 · Gautier · 2017 [cited by applicant]
US 20170039491A1 · Gauthier · 2017 [cited by applicant]
US 20170039576A1 · Gauthier · 2017 [cited by examiner]
US 20170061338A1 · Mack · 2017 [cited by applicant]
US 20170083916A1 · Fadli · 2017 [cited by applicant]
US 20170236214A1 · Wang · 2017 [cited by examiner]
US 20170278117A1 · Wallace et al. · 2017 [cited by applicant]
US 20180053127A1 · Boileau · 2018 [cited by applicant]
US 20180068012A1 · O'Connor et al. · 2018 [cited by applicant]
US 20180101854A1 · Jones-McFadden et al. · 2018 [cited by applicant]
US 20180189691A1 · Oehrle · 2018 [cited by applicant]
US 20180218385A1 · Gluck · 2018 [cited by applicant]
US 20180321830A1 · Calhoun et al. · 2018 [cited by applicant]
US 20190012629A1 · Yan · 2019 [cited by applicant]
US 20190034963A1 · George · 2019 [cited by applicant]
US 20190088153A1 · Bader-Natal et al. · 2019 [cited by applicant]
US 20190208060A1 · Piaggio · 2019 [cited by applicant]
US 20190251491A1 · Jones et al. · 2019 [cited by applicant]
US 20190259045A1 · Bower · 2019 [cited by applicant]
US 20190324825A1 · Schwartz et al. · 2019 [cited by applicant]
US 20190340714A1 · Bennett · 2019 [cited by applicant]
US 20190341027A1 · Vescovi et al. · 2019 [cited by applicant]
US 20190354990A1 · Trim et al. · 2019 [cited by applicant]
US 20200053030A1 · Moskowitz · 2020 [cited by applicant]
US 20200074878A1 · Hertsgaard · 2020 [cited by applicant]
US 20200097302A1 · Deutch · 2020 [cited by applicant]
US 20200127897A1 · Shultz · 2020 [cited by examiner]
US 20200134532A1 · Yamane · 2020 [cited by examiner]
US 20200135209A1 · Delfarah et al. · 2020 [cited by applicant]
US 20200160237A1 · Farooq · 2020 [cited by applicant]
US 20200287802A1 · Singh · 2020 [cited by applicant]
US 20200249581A1 · Petluru · 2020 [cited by applicant]
US 20200349581A1 · Petluru et al. · 2020 [cited by applicant]
US 20210117573A1 · Lewbel et al. · 2021 [cited by applicant]
US 20210150483A1 · Carlberg et al. · 2021 [cited by applicant]
US 20210278953A1 · Jang · 2021 [cited by applicant]
US 20210318891A1 · Purkait · 2021 [cited by applicant]
US 20210334472A1 · Shah et al. · 2021 [cited by applicant]
US 20210342181A1 · DSouza · 2021 [cited by examiner]
US 20210349865A1 · Shah · 2021 [cited by examiner]
US 20210398080A1 · Asanuma · 2021 [cited by applicant]
US 20220058540A1 · Carr · 2022 [cited by applicant]
CA 2388624C · 2011 [cited by applicant]
CN 101520784A · 2009 [cited by applicant]
EP 4200771A1 · 2023 [cited by applicant]
EP 4200772A1 · 2023 [cited by applicant]
EP 4200773A1 · 2023 [cited by applicant]
EP 4200786A1 · 2023 [cited by applicant]
WO 2015193640A1 · 2015 [cited by applicant]
WO 2020186300A1 · 2020 [cited by applicant]
WO 2021022232A1 · 2021 [cited by applicant]
WO 2021222320A1 · 2021 [cited by applicant]
WO 2022040145A1 · 2022 [cited by applicant]
WO 2022040150A1 · 2022 [cited by applicant]
WO 2022040156A1 · 2022 [cited by applicant]
Dyer, L., Henry, F., Lehmann, I., Lipof, G., Osmani, F., Parrott, D., . . . & Zahn, J. (2012). Scaling BPM adoption: From project to program with IBM business process manager. IBM Redbooks. (Year: 2012). [cited by examiner]
International Search Report issued in International Application No. PCT/US2021/046259, dated Nov. 11, 2021. [cited by applicant]
International Search Report issued in International Application No. PCT/US2021/046234, dated Nov. 22, 2021. [cited by applicant]
International Search Report issued in International Application No. PCT/US2021/046251, dated Dec. 8, 2021. [cited by applicant]
International Search Report issued in International Application No. PCT/US2021/046244, dated Nov. 22, 2021. [cited by applicant]
Non-Final Office Action issued in U.S. Appl. No. 17/405,300 on Nov. 26, 2021. [cited by applicant]
Non-Final Office Action issued in U.S. Appl. No. 17/405,283 on Dec. 7, 2021. [cited by applicant]
Non-Final Office Action issued in U.S. Appl. No. 17/405,271 on Dec. 10, 2021. [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,216, on Aug. 24, 2022. [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,235, on Jun. 23, 2022. [cited by applicant]
Final Office Action issued in related U.S. Appl. No. 17/405,283, on Jul. 1, 2022. [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,271 on Nov. 29, 2022. [cited by applicant]
Final Office Action issued in the related U.S. Appl. No. 17/405,235 on Jan. 17, 2023. [cited by applicant]
Non-Final Office Action issued in the related U.S. Appl. No. 17/405,300 on Jan. 13, 2023. [cited by applicant]
Non-Final Office Action issued in the related U.S. Appl. No. 17/405,185 on Mar. 31, 2023. [cited by applicant]
Final Office Action issued in the related U.S. Appl. No. 17/405,216 on Apr. 28, 2023. [cited by applicant]
International Preliminary Report issued in related Application Serial No. PCT/US2021/046234 on Mar. 2, 2023. [cited by applicant]
International Preliminary Report issued in related Application Serial No. PCT/US2021/046259 on Mar. 2, 2023. [cited by applicant]
International Preliminary Report issued in related Application Serial No. PCT/US2021/046251 on Mar. 2, 2023. [cited by applicant]
International Preliminary Report issued in related Application Serial No. PCT/US2021/046244 on Mar. 2, 2023. [cited by applicant]
Final Office Action issued in related U.S. Appl. No. 17/405,271 on Jun. 28, 2023. [cited by applicant]
Final Office Action issued in related U.S. Appl. No. 17/405,185 on Nov. 24, 2023. [cited by applicant]
Final Office Action issued in related U.S. Appl. No. 17/405,300 on Jan. 17, 2023. [cited by applicant]
Ma Dongbo et al, “Intelligent chatbot interaction system capable for sentimental analysis using hybrid machine learning algorithms,” 2023, Information Processing & Management, vol. 60, Issue 5, pp. 1-14 (Year: 2023). [cited by applicant]
Marquez, J. et al., ““Walking a Mile in the User's Shoes: Customer Journey Mapping as a Method to Understanding the User Experience,”” Internet Reference Services Quarterly, 20: 135-150, (2015). [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,264 on Sep. 14, 2023. [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,216 on Nov. 13, 2023. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,235 on Oct. 3, 2023. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,300 on Aug. 29, 2023. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,300 on Oct. 26, 2023. [cited by applicant]
Viktor Hangya and Richard Farkas et al. “A comparative empirical study on social media sentiment analysis over various genres and languages,” Jul. 2, 2016, Springer Science+Business Media Dordrecht 2016). (Year: 2016). [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,300 on Jul. 26, 2023. [cited by applicant]
Extended European Search Report issued in related Application Serial No. 21858949.7 on Jun. 24, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,264 on Jul. 9, 2024. [cited by applicant]
Extended European Search Report and Search Opinion issued in related Application Serial No. 21858945.5 on Aug. 8, 2024. [cited by applicant]
Farzindar, A., et al., “Natural Language Processing for Social Media”, Morgan & Claypool Publishers, Sep. 1, 2015, 112 pages. [cited by applicant]
Non-Final Office Action issued in related U.S. Appl. No. 17/405,185 on Oct. 2, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,264 on issue Date; Apr. 10, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,264 on issue Date; Apr. 25, 2024. [cited by applicant]
Extended European Search Report issued in related Application Serial No. 21858935.6 on Jul. 19, 2024. [cited by applicant]
Extended European Search Report issued in related Application Serial No. 21858940.6 on Jul. 22, 2024. [cited by applicant]
Final Office Action issued in related U.S. Appl. No. 17/405,216 on Aug. 16, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,264 on Aug. 5, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,264 on issue Aug. 26, 2024. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,185 on Feb. 26, 2025. [cited by applicant]
Saha, T., Saha, S., & Bhattacharyya, P. (2020). Towards sentiment aided dialogue policy learning for multi-intent conversations using hierarchical reinforcement learning. PLoS One, 15(7), e0235367. (Year: 2020). [cited by applicant]
K. Nagi, “Applying six sigma for quality assessment in a eLearning courseware production process,” International Conference on Computer and Communication Engineering (ICCCE'10), Kuala Lumpur, Malaysia, 2010, pp. 1-6 (Ye… [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,185 on May 22, 2025. [cited by applicant]
Notice of Allowance issued in related U.S. Appl. No. 17/405,216 on Apr. 2, 2025. [cited by applicant]