SYSTEM AND METHOD FOR IDENTIFYING AND PROVIDING PERSONALIZED SELF-HELP CONTENT WITH ARTIFICIAL INTELLIGENCE IN A CUSTOMER SELF-HELP SYSTEM
First Claim
1. A customer self-help system, comprising:
- at least one processor;
at least one communication channel coupled to the at least one processor; and
at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which when executed by any set of the at least one processor, perform a process for generating personalized self-help content that is responsive to a user query, the process including;
receiving service provider generated content data as a first portion of self-help content data;
receiving user generated content data as a second portion of the self-help content data;
storing the self-help content data in a self-help content data store;
applying one or more content processing algorithms to the self-help content data to generate self-help content characteristics data for the self-help content data,wherein the one or more content processing algorithms include one or more of a natural language process algorithm, a classifier algorithm, and a social algorithm;
receiving, with a customer self-help system, user query data representing a user query having a plurality of query terms;
applying one or more intent extraction algorithms to the user query data to generate query intent data representing a query intent for the user query, wherein the query intent data includes user query characteristics data representing a plurality of characteristics of the user query,wherein the one or more intent extraction algorithms include at least one of a natural language process algorithm and a classifier algorithm,wherein the natural language process algorithm includes a probabilistic topic model,wherein the classifier algorithm includes a predictive model;
determining self-help content characteristics data representing a plurality of characteristics of the self-help content data stored in the self-help content data store;
identifying relevant portions of the self-help content data by searching the self-help content data store for some of the self-help content characteristics data that match at least some of the user query characteristics data;
aggregating the relevant portions of the self-help content data into personalized self-help content data representing personalized self-help content that is relevant to and responsive to the user query; and
providing the personalized self-help content data to a client computing environment from which the user query data was received.
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Abstract
A customer self-help system employs artificial intelligence to generate personalized self-help content that is responsive to a user query submitted to the customer self-help system, according to one embodiment. The customer self-help system includes a pre-processor that characterizes and categorizes the self-help content into self-help content components, by using one or more content processing algorithms (e.g., a natural language processing algorithm), according to one embodiment. The customer self-help system includes an intent extractor engine that determines characteristics of the user query based on the user query and user profile data, according to one embodiment. The customer self-help system aggregates portions of the self-help content components into a personalized self-help content by matching characteristics of the user query with characteristics of the self-help content, according to one embodiment.
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Citations
37 Claims
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1. A customer self-help system, comprising:
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at least one processor; at least one communication channel coupled to the at least one processor; and at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which when executed by any set of the at least one processor, perform a process for generating personalized self-help content that is responsive to a user query, the process including; receiving service provider generated content data as a first portion of self-help content data; receiving user generated content data as a second portion of the self-help content data; storing the self-help content data in a self-help content data store; applying one or more content processing algorithms to the self-help content data to generate self-help content characteristics data for the self-help content data, wherein the one or more content processing algorithms include one or more of a natural language process algorithm, a classifier algorithm, and a social algorithm; receiving, with a customer self-help system, user query data representing a user query having a plurality of query terms; applying one or more intent extraction algorithms to the user query data to generate query intent data representing a query intent for the user query, wherein the query intent data includes user query characteristics data representing a plurality of characteristics of the user query, wherein the one or more intent extraction algorithms include at least one of a natural language process algorithm and a classifier algorithm, wherein the natural language process algorithm includes a probabilistic topic model, wherein the classifier algorithm includes a predictive model; determining self-help content characteristics data representing a plurality of characteristics of the self-help content data stored in the self-help content data store; identifying relevant portions of the self-help content data by searching the self-help content data store for some of the self-help content characteristics data that match at least some of the user query characteristics data; aggregating the relevant portions of the self-help content data into personalized self-help content data representing personalized self-help content that is relevant to and responsive to the user query; and providing the personalized self-help content data to a client computing environment from which the user query data was received. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A customer self-help system, comprising:
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at least one processor; at least one communication channel coupled to the at least one processor; and at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which when executed by any set of the at least one processor, perform a process for generating personalized self-help content that is responsive to a user query, the process including; storing self-help content data in a self-help content data store; receiving, with a customer self-help system, user query data representing a user query having a plurality of query terms; applying one or more intent extraction algorithms to the user query data to generate query intent data representing a query intent for the user query, wherein the query intent data includes user query characteristics data representing a plurality of characteristics of the user query; determining self-help content characteristics data representing a plurality of characteristics of the self-help content data stored in the self-help content data store; identifying relevant portions of the self-help content data by searching the self-help content data store for some of self-help content characteristics data that match at least some of the user query characteristics data; aggregating the relevant portions of the self-help content data into personalized self-help content data representing personalized self-help content that is relevant to and responsive to the user query; and providing the personalized self-help content data to a client computing environment from which the user query data was received. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A non-transitory computer-readable medium having a plurality of computer-executable instructions which, when executed by a processor, perform a method for generating personalized self-help content that is responsive to a user query, the instructions comprising:
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a self-help content data store that stores self-help content data; a pre-processor that analyzes the self-help content data and updates the self-help content data store with self-help content characteristics data to facilitate generating personalized self-help content data for a user query represented by user query data; a real-time process sub-system that receives the user query data and that generates the personalized self-help content data at least partially based on the user query data and at least partially based on the self-help content characteristics data, wherein the real-time process sub-system includes an intent extractor engine that identifies user query characteristics data at least partially based on the user query data and user profile data, a composer that extracts relevant portions of self-help content data from the self-help content data store, wherein the relevant portions of the self-help content data include self-help content characteristics data that are similar to characteristics of the user query characteristics data, wherein the composer aggregates the relevant portions of the self-help content data into the personalized self-help content data, wherein the real-time process sub-system provides the personalized self-help content data to a client computing system from which the user query data is received. - View Dependent Claims (24, 25, 26, 27, 28, 29, 30, 31)
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32. A customer self-help system, comprising:
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at least one processor; at least one communication channel coupled to the at least one processor; and at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which when executed by any set of the at least one processor, perform a process for generating personalized self-help content that is responsive to a user query, the process including; storing self-help content data in a self-help content data store; providing the self-help content data to one or more content processing algorithms to identify self-help content characteristics data; adding columns to tables in the self-help content data store to update the self-help content data store with the self-help content characteristics data; receiving, with a customer self-help system, user query data representing a user query having a plurality of query terms; applying one or more intent extraction algorithms to the user query data to identify user query characteristics data; identifying relevant portions of the self-help content data by searching the self-help content data store for self-help content characteristics data that match user query characteristics data; aggregating the relevant portions of the self-help content data into personalized self-help content data that is relevant to and responsive to the user query data; and providing the personalized self-help content data to a client computing environment from which the user query data was received. - View Dependent Claims (33, 34, 35, 36, 37)
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Specification