Automated identification and classification of complaint-specific user interactions using a multilayer neural network

摘要

Methods and apparatuses are described in which unstructured computer text is analyzed for identification and classification of complaint-specific user interactions. A data store receives unstructured computer text corresponding to current user interactions. A server filters the unstructured computer text to identify messages that comprise a potential complaint. For each message, the server: parses the message into sentences with words, converts each of the words in each sentence into a word vector, executes message classification models using the word vectors as input to generate a complaint probability value, combines the complaint probability values from each of the message classification models into an overall complaint probability value, classifies the message as a complaint when the overall complaint value exceeds a predetermined threshold value, and for each message classified as a complaint, routes the message to a client computing device that categorizes the message based upon one or more context features.