Invention Grant
- Patent Title: Story cycle time anomaly prediction and root cause identification in an agile development environment
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Application No.: US16211968Application Date: 2018-12-06
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Publication No.: US10540573B1Publication Date: 2020-01-21
- Inventor: Pu Li , Liang Chen , XiaoJia Yang , Zanyu Xie , Yulong Zhang
- Applicant: FMR LLC
- Applicant Address: US MA Boston
- Assignee: FMR LLC
- Current Assignee: FMR LLC
- Current Assignee Address: US MA Boston
- Agency: Proskauer Rose LLP
- Main IPC: G06F9/44
- IPC: G06F9/44 ; G06K9/62 ; G06N3/08 ; G06F11/36 ; G06N5/00 ; G06N20/00

Abstract:
Methods and apparatuses are described for automated computer text classification and routing using artificial intelligence transfer learning. A server captures historical story data from an Agile development tracking system. For each completed story, the server generates a vector based upon story-specific features and assigns a label to the vector based upon a cycle time associated with the story. The server trains a classification model using a neural network on the vectors and labels. The server captures new story data from the Agile development tracking system. For each new story, the server generates a vector based upon story-specific features and executes the trained model on the vector to generate a cycle time prediction for the new story. Based upon the cycle time prediction, the server identifies deficiencies in the new story and generates an alert message.
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