Feature recommendation based on user-generated content

Abstract

Provided is a system and method for automated recommendation of new features for addition to an item based on user-generated feedback. In one example, the method may include receiving, via a user interface, a search query associated with an object, retrieving user-generated content that describes the object based on the received search query, identifying, via a machine learning model, one or more features to be added to the object based on the retrieved user-generated content, and outputting identifiers of the one or more features to be added to the object via the user interface.

What is claimed is: 
     
         1 . A computing system comprising:
 a memory; and   a processor configured to
 receive, via a user interface, a search query associated with an object, 
 retrieve user-generated content that describes the object based on the received search query, 
 identifying, via execution of a machine learning model in the memory, one or more features to be added to the object based on the retrieved user-generated content, and 
 output identifiers of the one or more features to be added to the object via the user interface. 
   
     
     
         2 . The computing system of  claim 1 , wherein the processor is further configured to convert the user-generated content into a data structure that comprises a predefined format which includes values extracted from the user-generated content stored in predefined fields corresponding to object attributes. 
     
     
         3 . The computing system of  claim 1 , wherein the processor is further configured to identify a highest priority feature from among the identified one or more features to be added to the object based on an accumulation of user-generated content. 
     
     
         4 . The computing system of  claim 1 , wherein the search query comprises one or more of a name of the object, a name of a model of the object, and a description of the object, input via one or more fields of the user interface. 
     
     
         5 . The computing system of  claim 1 , wherein the processor is further configured to modify the search query to include an additional descriptive term associated with the object. 
     
     
         6 . The computing system of  claim 1 , wherein the processor is configured to distinguish, via execution of the machine learning model in the memory, user-generated comments that describe features from user-generated comments that do not describe features. 
     
     
         7 . The computing system of  claim 6 , wherein the processor is configured to identify a plurality of topics from the user-generated comments that describe features via a topic modeling algorithm. 
     
     
         8 . The computing system of  claim 7 , wherein the processor is configured to output descriptive identifiers of the plurality of topics as features to be added to the object, via the user interface. 
     
     
         9 . A method comprising:
 receiving, via a user interface, a search query associated with an object;   retrieving user-generated content that describes the object based on the received search query;   identifying, via a machine learning model, one or more features to be added to the object based on the retrieved user-generated content; and   outputting identifiers of the one or more features to be added to the object via the user interface.   
     
     
         10 . The method of  claim 9 , further comprising converting the user-generated content into a data structure that comprises a predefined format which includes values extracted from the user-generated content stored in predefined fields corresponding to object attributes. 
     
     
         11 . The method of  claim 9 , further comprising identifying a highest priority feature from among the identified one or more features to be added to the object based on an accumulation of user-generated content. 
     
     
         12 . The method of  claim 9 , wherein the search query comprises one or more of a name of the object, a name of a model of the object, and a description of the object, input via one or more fields of the user interface. 
     
     
         13 . The method of  claim 9 , further comprising modifying the search query to include an additional descriptive term associated with the object. 
     
     
         14 . The method of  claim 9 , wherein the identifying comprises distinguishing, via the machine learning model, user-generated comments that describe features from user-generated comments that do not describe features. 
     
     
         15 . The method of  claim 14 , wherein the identifying further comprises identifying a plurality of topics from the user-generated comments that describe features via a topic modeling algorithm. 
     
     
         16 . The method of  claim 15 , wherein the outputting comprises outputting descriptive identifiers of the plurality of topics as features to be added to the object, via the user interface. 
     
     
         17 . A non-transitory computer-readable medium comprising instructions which when executed by a processor cause a computer to perform a method comprising:
 receiving, via a user interface, a search query associated with an object;   retrieving user-generated content that describes the object based on the received search query;   identifying, via a machine learning model, one or more features to be added to the object based on the retrieved user-generated content; and   outputting identifiers of the one or more features to be added to the object via the user interface.   
     
     
         18 . The non-transitory computer-readable of  claim 17 , wherein the method further comprises converting the user-generated content retrieved via the API into a data structure that comprises a predefined format which includes values extracted from the user-generated content stored in predefined fields corresponding to object attributes. 
     
     
         19 . The non-transitory computer-readable of  claim 17 , wherein the method further comprises identifying a highest priority feature from among the identified one or more features to be added to the object based on an accumulation of user-generated content. 
     
     
         20 . The method of  claim 9 , wherein the identifying comprises distinguishing, via the machine learning model, user-generated comments that describe features from user-generated comments that do not describe features.