Method and system of continuous contextual user engagement

• US 9,460,155 B2
• Filed: 03/05/2014
• Issued: 10/04/2016
• Est. Priority Date: 03/06/2013
• Status: Active Grant

• Current Assignee: AppZen Inc.
• Original Assignee: AppZen Inc.
• Inventors: Verma, Kunal
• Primary Examiner(s): Stevens, Robert
• Application Number:
  US14/198,523
• Publication Number:
  US 20150254561A1
• Time in Patent Office: 944 Days
• Field of Search: 707/713
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24542 Plan optimisation
• CPC Class Codes: G06F 16/24564 Applying rules; Deductive queries

Abstract

In one exemplary aspect, a contextual user engagement system for automatically engaging in a conversation with a user is provided. A context manager manage, with at least one processor, the context of the conversation with a user. The context manager receives a user utterance, wherein the context manager calls the other modules of the contextual user engagement system to obtain information with respect to the user utterance. The context manager maintains a context object for a conversation with a user. The context manager automatically updates the context object based on an information detected by the other modules of contextual user engagement system. A content knowledge database stores a content knowledge of the contextual user engagement system. The content knowledge includes a history of interactions with the user. An information extraction engine extract information from a specified source based on a set of rules.

Claims

1. A context user engagement system for automatically engaging in a conversation with a user comprising:

a context manager that manages, with at least one processor, the context of the conversation with a user, wherein the context manager receives a user utterance,

wherein the context manager calls the other modules of the contextual user engagement system to obtain information with respect to the user utterance,

wherein the context manager maintains a context object for a conversation with a user, wherein the context manager automatically updates the context object based on an information detected by the other modules of contextual user engagement system;

a content knowledge database to store a content knowledge of the contextual user engagement system, wherein the content knowledge comprises a history of interactions with the user;

an information extraction engine that extracts information from a specified source based on a set of rules, wherein the information extraction engine extracts attributes and facets from the user utterance based on information extraction rules and patterns, wherein the information extraction engine assigns a probability to each extracted attribute based on a number of occurrences of the attribute, wherein the information extraction engine calculates a confidence value to the attribute, wherein the confidence value is defined as

2. The contextual user engagement system of claim 1, further comprising:

a query engine that comprises connectors for at least one of a database, an application programming interface engine, an enterprise system connect or an engine for analyzing unstructured data.

3. The contextual user engagement system of claim 1, further comprising:

an execution engine that generates a query plan and communicates the query plan to the query engine.

4. The contextual user engagement system of claim 1, wherein a context object update algorithm is utilized to update the context object.

5. The contextual user engagement system of claim 1, wherein a value occurs within a negated context, the confidence value is defined as:

6. The contextual user engagement system of claim 5, where the information extraction engine receives domain-specific rules and patterns from a user.

7. The contextual user engagement system of claim 6,

wherein an information extraction rule is based on the form of pattern variable and an action variable,

wherein the information extraction rule is fired when target string in the user utterance matches the pattern variable, and

wherein the action variable is used to specify a set of facts that are asserted in the context knowledge base when the rule is implemented.

8. The contextual user engagement system of claim 1, wherein the information in the context-knowledge base is represented as at one semantic model.

9. The contextual, user engagement system of claim 8, wherein the contextual topic engine utilizes a semantic similarity between flee context object and a candidate topic to determine a most likely topic to extract.

10. A contextual user engagement method for automatically engaging in a conversation with a user comprising:

receiving a user utterance with a context manager;

communicating, with the context manager, a user text a context identifier to an extraction engine, wherein the user text is obtained from the user utterance;

creating, with the context manager, a context object associated with the user utterance;

extracting, topics and attributes from the user text with the extraction engine, wherein the extraction engine extracts attributes and facets from the user utterance based on information extraction rules and patterns, wherein the extraction engine assigns a probability to each extracted attribute based on a number of occurrences of the attribute, wherein the extraction engine calculates a confidence value to the attribute, wherein the confidence value is defined as

11. The contextual user engagement method of claim 10, wherein the entity queried for additional information relevant to the system utterance comprises at least one of an SQL database, an application programming interface, an enterprise system connector or an engine for analyzing unstructured data.

12. The contextual user engagement method of claim 11, wherein the inference rule comprises one or more functions that obtains a premise, analyzes a syntax of the premise, and returns one or more conclusions.

13. A computerized system comprising:

a processor configured to execute instruction;

a memory containing instructions when executed on the processor, causes the processor to perform operations that;

receive a user utterance with a context manager;

communicate, with the context manager, a user text an context identifier to an extraction engine, wherein the user text is obtained from the user utterance;

create, with the context manager, a context object associated with the user utterance;

extract topics and attributes from the user text with the extraction engine, wherein the extraction engine assigns a probability to each extracted attribute based on a number of occurrences of the attribute, wherein the extraction engine calculates a confidence value to the attribute, wherein the confidence value is defined as

14. A computerized system of claim 13, wherein C(v) comprises a confidence in the information-extraction rule that extracted the attribute-value pair from the user utterance, wherein a(v) comprises an indicator function for whether a particular value occurred within a negated context, and wherein I(vi) comprises a collection of occurrences of a value extracted from the user utterance.