System and method for actionizing comments
AssigneePress Ganey Associates, Inc.
InventorsKyle Robertson, Taylor Turpen
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Abstract
A system and method for processing and actionizing structured and unstructured experience data is disclosed herein. In some embodiments, a system may include a natural language processing (NLP) engine configured to transform a data set into a plurality of concepts within a plurality of distinct contexts, and a data mining engine configured to process the relationships of the concepts and to identify associations and correlations in the data set. In some embodiments, the method may include the steps of receiving a data set, scanning the data set with an NLP engine to identify a plurality of concepts within a plurality of distinct contexts, and identifying patterns in the relationships between the plurality of concepts.
Claims20
A method for processing and actionizing experience data, the method comprising:
- receiving, by a server, a plurality of communications, wherein each of the plurality of communications comprises comment data, wherein the comment data comprises structured or unstructured data;
- parsing, by the server, the comment data from each of the plurality of communications for individual phrases to generate a plurality of phrases in response to receiving the plurality of communications;
- predicting, by the server with a natural language processing (NLP) engine, one or more annotations for each of the plurality of phrases based upon a machine learning score in response to parsing the comment data, wherein each of the one or more annotations comprises a sentiment of the corresponding phrase and a primary tag indicative of a subject matter of the corresponding phrase, other than sentiment
- determining, by the server, whether a certainty associated with the one or more annotations is less than a predetermined threshold based on the machine learning score;
- and
- predicting, by the server, the one or more annotations for the plurality of phrases based upon a reference score in response to determining that the certainty is less than the predetermined threshold.
A system for processing and actionizing experience data, the system comprising a server having a natural language processing (NLP) engine, wherein:
- the server is to:
- receive a plurality of communications, wherein each of the plurality of communications comprises comment data, wherein the comment data comprises structured or unstructured data;
- and
- parse the comment data from each of the plurality of communications for individual phrases to generate a plurality of phrases in response to receiving the plurality of communications;
- the NLP engine is to predict one or more annotations for each of the plurality of phrases based upon a machine learning score in response to parsing the comment data, wherein each of the one or more annotations comprises a sentiment of the corresponding phrase and a primary tag indicative of a subject matter of the corresponding phrase, other than sentiment
- determine whether a certainty associated with the one or more annotations is less than a predetermined threshold based on the machine learning score;
- and
- predict the one or more annotations for the plurality of phrases based upon a reference score in response to a determination that the certainty is less than the predetermined threshold.
One or more non-transitory computer-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause a server to:
- receive a plurality of communications, wherein each of the plurality of communications comprises comment data, wherein the comment data comprises structured or unstructured data;
- parse the comment data from each of the plurality of communications for individual phrases to generate a plurality of phrases in response to receiving the plurality of communications;
- predict one or more annotations for each of the plurality of phrases based upon a machine learning score in response to parsing the comment data, wherein each of the one or more annotations comprises a sentiment of the corresponding phrase and a primary tag indicative of a subject matter of the corresponding phrase, other than sentiment;
- determine whether a certainty associated with the one or more annotations is less than a predetermined threshold based on the machine learning score;
- and
- predict the one or more annotations for the plurality of phrases based upon a reference score in response to determining that the certainty is less than the predetermined threshold.
Dependencies are inferred from the claim text.