Invention Grant
- Patent Title: Data field extraction model training for a data intake and query system
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Application No.: US16945229Application Date: 2020-07-31
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Publication No.: US11663176B2Publication Date: 2023-05-30
- Inventor: Ram Sriharsha , Zhaohui Wang , Kristal Curtis , Abraham Starosta
- Applicant: Splunk Inc.
- Applicant Address: US CA San Francisco
- Assignee: Splunk Inc.
- Current Assignee: Splunk Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Knobbe Martens Olson & Bear LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/21 ; G06N3/08 ; G06K9/62 ; G06F16/25

Abstract:
Systems and methods are described for training an artificial intelligence model to extract one or more data fields from a log. For example, the artificial intelligence model may be a neural network. The neural network may be trained using training data obtained by iterating through a plurality of logs using active learning, and selecting a subset of the logs in the plurality to be labeled by a user. For example, the selected subset of logs may be logs that are not similar to other logs already labeled by a user. The user may be prompted to label the selected subset of logs to identify one or more data fields to extract. Once the selected subset of logs are labeled, these labeled logs can be used as the training data to train the neural network.
Public/Granted literature
- US20220035775A1 DATA FIELD EXTRACTION MODEL TRAINING FOR A DATA INTAKE AND QUERY SYSTEM Public/Granted day:2022-02-03
Information query