Systems and methods for navigating nodes in channel based chatbots using natural language understanding
The disclosed systems and methods join a user to a primary communication channel that is associated with an automated human interface module. The automated human interface module includes a plurality of nodes. A message including a text communication is posted by the user and sent to a decision module associated with a plurality of classifiers. The decision module is configured to identify a node that best matches the text communication in accordance with the plurality of classifiers. Each respective classifier produces a respective classifier result thereby producing a plurality of classifier results. Each respective classifier result identifies a respective node of the plurality of nodes best matching the text communication. The plurality of classifier results is collectively considered, and the node best matching the text communication is identified and the text communication is sent to the identified node.
1. A server system, comprising:
one or more processors;
memory; and
one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions for:
A) receiving a plurality of data elements, wherein each data element in the plurality of data elements is (i) associated with a user and (ii) published, in electronic form, by one or more sources other than the user;
B) responsive to receiving the plurality of data elements, sending the plurality of data elements to a decision module associated with a plurality of classifiers, the decision module configured to identify a first node within the plurality of nodes, wherein the first node is a node that best matches with a respective characteristic in a plurality of characteristics in accordance with the plurality of classifiers;
C) processing, with each respective classifier of the plurality of classifiers, the plurality of data elements, thereby producing a respective classifier result for each respective classifier in the plurality of classifiers, and thereby producing a plurality of classifier results, wherein each respective classifier result in the plurality of classifier results identifies a respective node of the plurality of nodes that best matches with the subset of data elements with a corresponding characteristic in the plurality of characteristics in accordance with a corresponding classifier in the plurality of classifiers;
D) collectively considering, with the decision module, the plurality of classifier results, thereby identifying the first node within the plurality of nodes; and
E) updating a corresponding user profile associated with the user in accordance with the corresponding characteristic through the identifying the first node, thereby producing an updated corresponding user profile; and
F) joining the user to a primary communication channel that is associated with an automated human interface module based at least on the corresponding characteristic of the updated corresponding user profile, wherein the primary communication channel facilitates electronic communication between a corresponding enterprise data source and a remote user device associated with the user.
2. The server system of claim 1 , wherein the collectively considering the plurality of classifier results D) includes determining a majority vote among the plurality of classifier results.
3. The server system of claim 1 , wherein the collectively considering the plurality of classifier results D) includes determining a weighed vote among the plurality of classifier results.
4. The server system of claim 1 , wherein the plurality of classifiers includes six or more classifiers.
5. The server system of claim 1 , wherein each classifier in the plurality of classifiers is independently selected from the group consisting of: Naïve Bayes, decision tree, logistic regression, support vector machine, random forest, and artificial neural network.
6. The server system of claim 1 , wherein a classifier in the plurality of classifiers is a support vector machine, a clustering algorithm, a neural network, a decision tree, a logistic regression, a linear regression module, or a k-nearest neighbor classifier.
7. The server system of claim 1 , wherein processing the plurality of data elements C) includes processing the plurality of data elements to identify one or more of a name, an age, an emoticon, a date, a gender, a physical address, an electronic address, a quote, a sport, a team, a spoken language, a genre of music, or a combination thereof.
8. The server system of claim 1 , wherein processing the plurality of data elements C) includes a first processing step that comprises:
processing the first text communication with each respective classifier of a first subset of the plurality of classifiers;
producing a respective first classifier result, with each respective classifier of the first subset of the plurality of classifiers, thereby producing a first subset of the plurality of first classifier results;
collectively considering, with the decision module, the first subset of the first classifier results; and
identifying, based on the collectively considering the first subset of the first classifier results, a first parameter associated with the first text communication.
9. The server system of claim 1 , further including sending, to the remote user device, a first message and presenting by a display of the remote user device the first message.
10. The server system of claim 1 , where in the one or more sources comprises an anonymous source, an authenticated source, or a combination thereof.
11. The server system of claim 1 , wherein the plurality of data elements comprises one or more data elements authored by the user.
12. The server system of claim 1 , wherein the plurality of characteristics comprises one or more user demographic characteristics, one or more geographic characteristics, one or more historical characteristics, one or more pattern-based characteristics, one or more sentiment characteristics, one or more intent characteristics, one or more tone characteristics, one or more personalized results uniquely associated with the user, or a combination thereof.
13. The server system of claim 1 , wherein the plurality of characteristics comprises a future best action by the automated human interface module, a workflow for the automated human interface module, a survey provided by the automated human interface module for the user, or a combination thereof.
14. The server system of claim 1 , wherein the plurality of characteristics comprises one or more customer relationship management characteristics.
15. The server system of claim 1 , wherein the updating the corresponding user profile further comprises sending, to the corresponding enterprise data source, the updated corresponding user profile.
16. The server system of claim 15 , further comprising display, at a display of a remote user device associated with the corresponding enterprise data source, the updated corresponding user profile.
17. The server system of claim 1 , further comprising, prior to the joining F), sending, to the remote user device associated with the user, a first message providing access to the primary communication channel.
18. A non-transitory computer readable storage medium stored on a computing device, the computing device comprising, a display, one or more processors, and memory storing one or more programs for execution by the one or more processors, wherein the one or more programs singularly or collectively comprise instructions for running an application on the computing device that executes a method comprising:
A) receiving a plurality of data elements, wherein each data element in the plurality of data elements is (i) associated with a user and (ii) published, in electronic form, by one or more sources other than the user;
B) responsive to receiving the plurality of data elements, sending the plurality of data elements to a decision module associated with a plurality of classifiers, the decision module configured to identify a first node within the plurality of nodes, wherein the first node is a node that best matches with a respective characteristic in a plurality of characteristics in accordance with the plurality of classifiers;
C) processing, with each respective classifier of the plurality of classifiers, the plurality of data elements, thereby producing a respective classifier result for each respective classifier in the plurality of classifiers, and thereby producing a plurality of classifier results, wherein each respective classifier result in the plurality of classifier results identifies a respective node of the plurality of nodes that best matches with the subset of data elements with a corresponding characteristic in the plurality of characteristics in accordance with a corresponding classifier in the plurality of classifiers;
D) collectively considering, with the decision module, the plurality of classifier results, thereby identifying the first node within the plurality of nodes; and
E) updating a corresponding user profile associated with the user in accordance with the corresponding characteristic through the identifying the first node, thereby producing an updated corresponding user profile; and
F) joining the user to a primary communication channel that is associated with an automated human interface module based at least on the corresponding characteristic of the updated corresponding user profile, wherein the primary communication channel facilitates electronic communication between a corresponding enterprise data source and a remote user device associated with the user.
19. A method comprising:
A) receiving a plurality of data elements, wherein each data element in the plurality of data elements is (i) associated with a user and (ii) published, in electronic form, by one or more sources other than the user;
B) responsive to receiving the plurality of data elements, sending the plurality of data elements to a decision module associated with a plurality of classifiers, the decision module configured to identify a first node within the plurality of nodes, wherein the first node is a node that best matches with a respective characteristic in a plurality of characteristics in accordance with the plurality of classifiers;
C) processing, with each respective classifier of the plurality of classifiers, the plurality of data elements, thereby producing a respective classifier result for each respective classifier in the plurality of classifiers, and thereby producing a plurality of classifier results, wherein each respective classifier result in the plurality of classifier results identifies a respective node of the plurality of nodes that best matches with the subset of data elements with a corresponding characteristic in the plurality of characteristics in accordance with a corresponding classifier in the plurality of classifiers;
D) collectively considering, with the decision module, the plurality of classifier results, thereby identifying the first node within the plurality of nodes; and
E) updating a corresponding user profile associated with the user in accordance with the corresponding characteristic through the identifying the first node, thereby producing an updated corresponding user profile; and
F) joining the user to a primary communication channel that is associated with an automated human interface module based at least on the corresponding characteristic of the updated corresponding user profile, wherein the primary communication channel facilitates electronic communication between a corresponding enterprise data source and a remote user device associated with the user.