Method and system for automatically generating a response to a user query
First Claim
1. A method for automatically generating a response to a user query, the method comprising:
- receiving, by a response generating system, the user query from a computing device associated with an end user;
determining, by the response generating system, whether the user query belongs to at least one domain from a plurality of predefined domains;
determining, when the user query belongs to the at least one domain, by the response generating system, goal data and a problem category of the user query, wherein determining the goal data comprises determining one or more features of one or more tokens based on Part-Of-Speech (POS) tags, wherein the one or more features comprise satisfying features that indicate steps successfully performed by the end user for resolving a problem;
detecting, by the response generating system, a problem node and one or more problem sub-nodes associated with the user query by parsing a predefined knowledge graph corresponding to a category of the at least one domain, based on the goal data and the problem category;
comparing, by the response generating system, each of the one or more problem sub-nodes with the satisfying features for semantic similarity;
removing, upon comparison, by the response generating system, the one or more problem sub-nodes that are semantically similar to the satisfying features;
providing, upon removal, by the response generating system, at least one of open-ended questions and closed-ended questions based on the one or more problem sub-nodes of the problem node to the computing device to receive a feedback for at least one of the open-ended questions and the closed-ended questions from the end user; and
displaying, by the response generating system, the response to the user query extracted from one of the one or more problem sub-nodes to the end user based on the feedback;
wherein determining the problem category comprises;
creating, by the response generating system, a vocabulary file comprising each of one or more words in the user query and an Identifier (ID) corresponding to each of one or more words in the user query;
assigning, by the response generating system a weightage for each of the one or more words in the user query;
filtering, by the response generating system, the one or more words from the user query based on the weightage;
generating, by the response generating system, one or more feature vectors by assigning a feature vector weightage to each of the one or more filtered words based on one or more parameters; and
comparing, by the response generating system, each of the one or more feature vectors with each of the one or more predefined feature vectors related to the at least one domain to determine the problem category.
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Abstract
Disclosed subject matter relates to virtual assistance that includes a method and system for automatically generating response to a user query without language constraints. A response generating system receives the user query from a computing device associated with an end user and determines whether the user query belongs to at least one domain to determine goal data and a problem category of the user query. Further, a problem node associated with the user query is detected from problem nodes by parsing a predefined knowledge graph based on the goal data and the problem category. Furthermore, questions are provided based on problem sub-nodes of the problem node to the computing device to receive a feedback. The response to the user query extracted from the one of the problem sub-nodes is displayed to the end user based on the feedback. The present disclosure is highly scalable, reusable and requires minimal human supervision.
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Citations
27 Claims
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1. A method for automatically generating a response to a user query, the method comprising:
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receiving, by a response generating system, the user query from a computing device associated with an end user; determining, by the response generating system, whether the user query belongs to at least one domain from a plurality of predefined domains; determining, when the user query belongs to the at least one domain, by the response generating system, goal data and a problem category of the user query, wherein determining the goal data comprises determining one or more features of one or more tokens based on Part-Of-Speech (POS) tags, wherein the one or more features comprise satisfying features that indicate steps successfully performed by the end user for resolving a problem; detecting, by the response generating system, a problem node and one or more problem sub-nodes associated with the user query by parsing a predefined knowledge graph corresponding to a category of the at least one domain, based on the goal data and the problem category; comparing, by the response generating system, each of the one or more problem sub-nodes with the satisfying features for semantic similarity; removing, upon comparison, by the response generating system, the one or more problem sub-nodes that are semantically similar to the satisfying features; providing, upon removal, by the response generating system, at least one of open-ended questions and closed-ended questions based on the one or more problem sub-nodes of the problem node to the computing device to receive a feedback for at least one of the open-ended questions and the closed-ended questions from the end user; and displaying, by the response generating system, the response to the user query extracted from one of the one or more problem sub-nodes to the end user based on the feedback; wherein determining the problem category comprises; creating, by the response generating system, a vocabulary file comprising each of one or more words in the user query and an Identifier (ID) corresponding to each of one or more words in the user query; assigning, by the response generating system a weightage for each of the one or more words in the user query; filtering, by the response generating system, the one or more words from the user query based on the weightage; generating, by the response generating system, one or more feature vectors by assigning a feature vector weightage to each of the one or more filtered words based on one or more parameters; and comparing, by the response generating system, each of the one or more feature vectors with each of the one or more predefined feature vectors related to the at least one domain to determine the problem category. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A response generating system for automatically generating a response to a user query, the response generating system comprising:
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a processor; and a memory communicatively coupled to the processor, wherein the memory stores the processor-executable instructions, which, on execution, causes the processor to; receive the user query from a computing device associated with an end user; determine whether the user query belongs to at least one domain from a plurality of predefined domains; determine, when the user query belongs to the at least one domain, by the response generating system, goal data and a problem category of the user query, wherein determining the goal data comprises determining one or more features of one or more tokens based on Part-Of-Speech (POS) tags, wherein the one or more features comprise satisfying features that indicate steps successfully performed by the end user for resolving a problem; detect a problem node and one or more problem sub-nodes associated with the user query by parsing a predefined knowledge graph corresponding to a category of the at least one domain, based on the goal data and the problem category; compare each of the one or more problem sub-nodes with the satisfying features for semantic similarity; remove, upon comparison, the one or more problem sub-nodes that are semantically similar to the satisfying features; provide, upon removal, at least one of open-ended questions and closed-ended questions based on the one or more problem sub-nodes of the problem node to the computing device to receive a feedback for at least one of the open-ended questions and the closed-ended questions from the end user; and display the response to the user query extracted from one of the one or more problem sub-nodes to the end user based on the feedback; wherein to determine the problem category, the instructions cause the processor to; create a vocabulary file comprising each of one or more words in the user query and an Identifier (ID) corresponding to each of one or more words in the user query; assign a weightage for each of the one or more words in the user query; filter the one or more words from the user query based on the weightage; generate one or more feature vectors by assigning a feature vector weightage to each of the one or more filtered words based on one or more parameters; and compare each of the one or more feature vectors with each of the one or more predefined feature vectors related to the at least one domain to determine the problem category. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26)
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22. The response generating system as claimed in 14, wherein the one or more parameters comprise at least one of presence of predefined-domain related words and cue words representing the at least one domain in the user query and range of the user query.
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27. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a response generating system to automatically generate a response to a user query by performing operations comprising:
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receiving the user query from a computing device associated with an end user; determining whether the user query belongs to at least one domain from a plurality of predefined domains; determining when the user query belongs to the at least one domain, by the response generating system, goal data and a problem category of the user query, wherein determining the goal data comprises determining one or more features of one or more tokens based on Part-Of-Speech (POS) tags, wherein the one or more features comprise satisfying features that indicate steps successfully performed by the end user for resolving a problem ; detecting a problem node and one or more problem sub-nodes associated with the user query by parsing a predefined knowledge graph corresponding to a category of the at least one domain, based on the goal data and the problem category; comparing each of the one or more problem sub-nodes with the satisfying features for semantic similarity; removing, upon comparison, the one or more problem sub-nodes that are semantically similar to the satisfying features; providing, upon removal, at least one of open-ended questions and closed-ended questions based on the one or more problem sub-nodes of the problem node to the computing device to receive a feedback for at least one of the open-ended questions and the closed-ended questions from the end user; and displaying the response to the user query extracted from one of the one or more problem sub-nodes to the end user based on the feedback; wherein to determining the problem category comprises; creating a vocabulary file comprising each of one or more words in the user query and an Identifier (ID) corresponding to each of one or more words in the user query; assigning a weightage for each of the one or more words in the user query; filtering the one or more words from the user query based on the weightage; generating one or more feature vectors by assigning a feature vector weightage to each of the one or more filtered words based on one or more parameters; and comparing each of the one or more feature vectors with each of the one or more predefined feature vectors related to the at least one domain to determine the problem category.
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Specification