US 11,943,178 B2
Systems and methods for multi-channel messaging and communication
Anil K. Annadata, Saratoga, CA (US); Arun Balasubramanyam, Fremont, CA (US); and Sanjin Tulac, Mountain View, CA (US)
Assigned to CodeObjects Inc., Milpitas, CA (US)
Filed by CodeObjects Inc., Milpitas, CA (US)
Filed on Dec. 28, 2022, as Appl. No. 18/089,856.
Application 18/089,856 is a continuation of application No. 17/179,303, filed on Feb. 18, 2021, abandoned.
Application 17/179,303 is a continuation of application No. 16/412,332, filed on May 14, 2019, granted, now 10,958,600, issued on Mar. 23, 2021.
Claims priority of provisional application 62/675,071, filed on May 22, 2018.
Claims priority of provisional application 62/673,508, filed on May 18, 2018.
Prior Publication US 2023/0171208 A1, Jun. 1, 2023
Int. Cl. H04L 51/02 (2022.01); H04L 51/04 (2022.01)
CPC H04L 51/02 (2013.01) [H04L 51/04 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method for providing automated conversation across multiple communication channels associated with a user, the method comprising:
selecting a first communication channel from the multiple communication channels;
receiving, via the first communication channel, a first user input as part of a conversation with a chatbot, the chatbot including a communication data structure including a plurality of communication paths, and a plurality of communication identities,
wherein each of the plurality of communication paths comprises a plurality of units, and
wherein at least one of the plurality of units is coded with instructions to navigate the conversation among different communication paths;
generating a communication identity based on the first user input,
wherein the communication identity includes a plurality of identity elements;
selecting a communication path based on the first user input, wherein selecting the communication path includes:
comparing the generated communication identity with the plurality of communication identities in the communication data structure to determine a match;
when there is no match between the generated communication identity with the plurality of communication identities in the communication data structure,
selecting, via a selection algorithm, a unit within the plurality of units,
wherein, selecting, via a selection algorithm, a unit within the plurality of units includes:
determining one or more communication identities stored within the communication data structure that may approximately match the generated communication identity,
providing the user with one or more feedbacks associated with one or more approximately matched communication identities,
receiving, from the user, a selected feedback from the one or more feedbacks associated with one or more approximately matched communication identities, and
selecting the unit associated with the selected communication identities,
wherein the selection algorithm is a machine learning algorithm, the machine learning algorithm including a computer-implemented method of selecting a unit within the plurality of units including:
receiving an input dataset comprising a user's historical communication data and/or other users' historical communication data;
determining a user's expected feedback; and
producing an output dataset comprising a unit selection associated with the user's expected feedback;
selecting a unit associated with the matched communication identity within the plurality of identities; and
generating a first feedback in response to the first user input according to the selected communication path.