- Patent Title: Multi-task conditional random field models for sequence labeling
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Application No.: US14564138Application Date: 2014-12-09
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Publication No.: US09785891B2Publication Date: 2017-10-10
- Inventor: Arvind Agarwal , Saurabh Kataria
- Applicant: XEROX CORPORATION
- Applicant Address: US TX Dallas
- Assignee: Conduent Business Services, LLC
- Current Assignee: Conduent Business Services, LLC
- Current Assignee Address: US TX Dallas
- Agency: Jones Robb PLLC
- Main IPC: G06N99/00
- IPC: G06N99/00 ; G06Q30/00

Abstract:
Embodiments of a computer-implemented method for automatically analyzing a conversational sequence between multiple users are disclosed. The method includes receiving signals corresponding to a training dataset including multiple conversational sequences; extracting a feature from the training dataset based on predefined feature categories; formulating multiple tasks for being learned from the training dataset based on the extracted feature, each task related to a predefined label; and providing a model for each formulated task, the model including a set of parameters common to the tasks. The set includes an explicit parameter, which is explicitly shared with each of the formulated tasks. The method further includes optimizing a value of the explicit parameter to create an optimized model; creating a trained model for the formulated tasks using the optimized value of the explicit parameter; and assigning predefined labels for the formulated tasks to a live dataset based on the corresponding trained model.
Public/Granted literature
- US20160162804A1 MULTI-TASK CONDITIONAL RANDOM FIELD MODELS FOR SEQUENCE LABELING Public/Granted day:2016-06-09
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