Categorization of user interactions into predefined hierarchical categories
Assignee24/7 Customer, Inc.
InventorsRavi VIJAYARAGHAVAN, Vaibhav Srivastava, R. Mathangi Sri, Nitin Kumar Hardeniya
Life of this patent
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Abstract
User interactions are categorized into predefined hierarchical categories by classifying user interactions, such as queries, during a user interaction session by labeling text data into predefined hierarchical categories, and building a scoring model. The scoring model is then executed on untagged user interaction data to classify the user interactions into either action-based or information-based interactions.
Claims18
A computer implemented method for categorization of user interactions into predefined hierarchical categories, comprising:
- providing a processor configured for classifying user interactions during a user interaction session by labeling text data into predefined hierarchical categories, and building a scoring model;
- and
- said processor executing said scoring model on untagged user interaction data to classify said user interactions into either action-based or information-based interactions.
An apparatus for categorization of user interactions into predefined hierarchical categories, comprising:
- a processor programmed with machine instructions which, when executed classify user interactions during a user interaction session by labeling text data points into predefined hierarchical categories, segregating issues, and building a scoring model;
- and
- said processor executing said scoring model based upon data within said scoring model and untagged user interaction data to classify said user interactions into either action-based or information-based interactions.
A method for query categorization into predefined hierarchical categories, comprising:
- an agent receiving from a user either of an information or action oriented request during an interaction session;
- providing a processor configured to implement a text filter for filtering relevant sections of text in said interaction session;
- said processor configured to implement text parser for parsing said text and for extracting important features from the interaction session;
- said processor building a category tree to categorize different kinds of issues in said interaction session to segregate said issues into different categories;
- during a training phase:
- once a domain specific category tree is built, defining categories and creating rules, wherein said rules help to extract relevant features during said interaction session;
- once said rules are created, extracting relevant features;
- during a pre-processing session, generalizing said text by replacing specific words with standard words;
- creating a scoring model;
- and
- generating a matrix based on said score;
- wherein said matrix is given a score based on the relevance of the matrix generated;
- and
- wherein said score obtained is based on a comparison between the rules created and the category tree.
Dependencies are inferred from the claim text.