Invention Grant
- Patent Title: Displaying text classification anomalies predicted by a text classification model
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Application No.: US16454773Application Date: 2019-06-27
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Publication No.: US11074414B2Publication Date: 2021-07-27
- Inventor: Ming Tan , Saloni Potdar , Lakshminarayanan Krishnamurthy
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agent David K. Mattheis; Maeve M. Carpenter
- Main IPC: G06F40/289
- IPC: G06F40/289 ; G06F3/0482 ; G06K9/62 ; G06F40/166

Abstract:
A test controller submits testing phrases to a text classifier and receives, from the text classifier, classification labels each comprising one or more respective heatmap values each associated with a separate word. The test controller aligns each of the classification labels corresponding with a respective testing phrase. The test controller identifies one or more anomalies of a selection of one or more classification labels that are different from an expected classification label for the respective testing phrase. The test controller outputs a graphical representation in a user interface of the selection of one or more classification labels and one or more respective testing phrases with visual indicators based on one or more respective heatmap values.
Public/Granted literature
- US20200327194A1 DISPLAYING TEXT CLASSIFICATION ANOMALIES PREDICTED BY A TEXT CLASSIFICATION MODEL Public/Granted day:2020-10-15
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