Systems and methods for processing natural language queries
First Claim
Patent Images
1. A method for processing natural language queries comprising:
- obtaining a natural language query from a user;
generating at least one semantic token from the natural language query;
identifying data in a knowledge base using the at least one semantic token;
interpreting the identified data based on an intention associated with the user, wherein the intention is expressed in a personalized policy, and wherein interpreting the identified data comprises;
recognizing an uncertainty in the natural language query, wherein the uncertainty comprises at least one of;
a lack of identified data in the knowledge base;
the natural language query including a series of dependent commands without information associated with a sequence of the commands; and
the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; and
resolving the uncertainty based on the user intention, wherein resolving the uncertainty comprises;
establishing the personalized policy for the user;
applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data comprising data relating to the user'"'"'s location and sensor data;
receiving feedback from the user relating to the application of the personalized policy; and
re-configuring the personalized policy based on the feedback; and
actuating the interpreted data.
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Abstract
Methods and systems are provided for processing natural language queries. Such methods and systems may receive a natural language query from a user and generate corresponding semantic tokens. Information may be retrieved from a knowledge base using the semantic tokens. Methods and systems may leverage an interpretation module to process and analyze the retrieved information in order to determine an intention associated with the natural language query. Methods and systems may leverage an actuation module to provide results to the user, which may be based on the determined intention.
415 Citations
48 Claims
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1. A method for processing natural language queries comprising:
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obtaining a natural language query from a user; generating at least one semantic token from the natural language query; identifying data in a knowledge base using the at least one semantic token; interpreting the identified data based on an intention associated with the user, wherein the intention is expressed in a personalized policy, and wherein interpreting the identified data comprises; recognizing an uncertainty in the natural language query, wherein the uncertainty comprises at least one of; a lack of identified data in the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; and resolving the uncertainty based on the user intention, wherein resolving the uncertainty comprises; establishing the personalized policy for the user; applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data comprising data relating to the user'"'"'s location and sensor data; receiving feedback from the user relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and
actuating the interpreted data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for processing natural language queries comprising:
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obtaining a natural language query from a user; generating at least one semantic token from the natural language query; identifying data in a knowledge base using the at least one semantic token; determining an intention associated with the user based on the identified data, wherein the intention is expressed in a personalized policy and, wherein determining the intention associated with the user comprises; recognizing an uncertainty in the natural language query, wherein the uncertainty comprises at least one of; a lack of identified data in the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; and resolving the uncertainty, wherein resolving the uncertainty comprises; establishing the personalized policy for the user; applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data comprising data relating to the user'"'"'s location and sensor data; receiving feedback from the user relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and providing information that is relevant to the natural language query to the user based on the determined intention. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A method for processing natural language queries comprising:
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obtaining a natural language query from a source; retrieving data that is potentially relevant to the natural language query from a knowledge base; determining an intention associated with the natural language query, wherein the intention is expressed in a personalized policy; and processing the potentially relevant data in accordance with the intention so as to identify actually relevant data from the potentially relevant data, wherein processing the potentially relevant data comprises; establishing the personalized policy for the user; applying the personalized policy in conjunction with contextual data obtained from the user to identify the actually relevant data from the potentially relevant data, the contextual data comprising data relating to the user'"'"'s location and sensor data; receiving feedback from the user relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and providing the actually relevant data to the source. - View Dependent Claims (18, 19, 20, 21)
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22. A method for processing natural language queries, comprising:
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obtaining a natural language query from a user; generating at least one semantic token from the natural language query; identifying data in a knowledge base using the at least one semantic token; identifying an uncertainty in the natural language query, wherein the uncertainty comprises at least one of; a lack of identified data in the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; determining an intention associated with the user based on the identified data, wherein the intention is expressed in a personalized policy; and resolving the identified uncertainty based on the determined intention, wherein resolving the uncertainty comprises; establishing the personalized policy for the user; applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data relating to the user'"'"'s location and sensor data; receiving feedback from the user relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback. - View Dependent Claims (23)
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24. A system for processing natural language queries, comprising:
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means for obtaining a natural language query from a user; means for generating at least one semantic token from the natural language query; means for identifying data in a knowledge base using the at least one semantic token; means for determining an intention associated with the user based on the identified data, wherein the intention is expressed in a personalized policy, and wherein means for determining an intention associated with the user comprises; means for recognizing an uncertainty in the natural language query, wherein the uncertainty comprises at least one of; a lack of identified data in the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; and means for resolving the uncertainty, the means for resolving the uncertainty comprising; means for establishing the personalized policy for the user; means for applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty the contextual data comprising data relating to the user'"'"'s location and sensor data; means for receiving feedback from the user relating to the application of the personalized policy; and means for re-configuring the personalized policy based on the feedback; and means for providing information that is relevant to the natural language query to the user based on the determined intention.
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25. A system for processing natural language queries, comprising:
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means for obtaining a natural language query from a user; means for generating at least one semantic token from the natural language query; means for identifying data in a knowledge base using the at least one semantic token; means for identifying an uncertainty in the natural language query, wherein the uncertainty comprises at least one of; a lack of identified data in the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the identified data including a plurality of conceptually similar elements that relate to a generated semantic token; means for determining an intention associated with the user based on the identified data, wherein the intention is expressed in a personalized policy; and means for resolving the identified uncertainty based on the determined intention, wherein the means for resolving the uncertainty comprises; means for establishing the personalized policy for the user; means for applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data comprising data relating to the user'"'"'s location and sensor data; means for receiving feedback from the user relating to the application of the personalized policy; and means for re-configuring the personalized policy based on the feedback.
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26. A natural language query processing system, comprising:
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an interface module configured to receive a natural language query; a tokenizing module configured to generate at least one semantic token based on the received natural language query; a searching module configured to retrieve information from a knowledge base using the at least one semantic token; an interpretation module configured to; identify an uncertainty associated with the natural language query, wherein the uncertainty comprises at least one of; a lack of retrieved information from the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the retrieved information including a plurality of conceptually similar elements that relate to a generated semantic token; and resolve the uncertainty, wherein resolving the uncertainty comprises; establishing a personalized policy, applying the personalized policy in conjunction with contextual data obtained from the user to resolve the uncertainty, the contextual data comprising data relating to the user'"'"'s location and sensor data, receiving feedback relating to the application of the personalized policy, and re-configuring the personalized policy based on the feedback, and process the retrieved information so as to resolve the uncertainty based on an intention associated with the received natural language query, wherein the intention is expressed in the personalized policy; and an actuation module configured to translate the processed information into a system-actionable command. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35)
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36. A natural language query processing system, comprising:
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an interface module configured to receive a natural language query; a tokenizing module configured to generate at least one semantic token based on the received natural language query; a searching module configured to retrieve information from a knowledge base using the at least one semantic token; an interpretation module configured to; determine an intention associated with the received natural language query, wherein the intention is expressed in a personalized policy, and process the retrieved information in accordance with the intention, wherein the interpretation module processes the retrieved information by; establishing the personalized policy; applying the personalized policy in conjunction with contextual data obtained from the user to resolve an uncertainty in the natural language query, the contextual data comprising data relating to the user'"'"'s location and sensor data; receiving feedback relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and an actuation module configured to provide the processed information to a user. - View Dependent Claims (37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47)
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48. A computer-readable medium containing instructions for controlling a computer system coupled to a network to perform a method, the computer system having a processor for executing the instructions, the method comprising:
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obtaining a natural language query from a source; retrieving data that is potentially relevant to the natural language query from a knowledge base; determining an intention associated with the natural language query, wherein the intention is expressed in a personalized policy; and processing the potentially relevant data in accordance with the intention so as to separate the potentially relevant data into actually relevant data and actually irrelevant data, wherein the interpretation module processing the potentially relevant data comprises; establishing the personalized policy; applying the personalized policy in conjunction with contextual data obtained from the source to resolve an uncertainty in the natural language query, the contextual data comprising data relating to location and sensor data, wherein the uncertainty comprises at least one of; a lack of retrieved data from the knowledge base; the natural language query including a series of dependent commands without information associated with a sequence of the commands; and the retrieved data including a plurality of conceptually similar elements that relate to a generated semantic token; receiving feedback relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and providing the actually relevant data to the source.
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Specification