- 专利标题： Related content identification for different types of machine-generated data
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申请号： US17073024申请日： 2020-10-16
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公开(公告)号： US11250069B1公开(公告)日： 2022-02-15
- 发明人: Amy Katherine Hunnel Bianchi , Sonya Chang , Park Kittipatkul , Patrick Lin , Sarah Matarese , Clark Mullen , Alexandra Victoria Nuttbrown , Danika Patrick , Justin Smith , Harsh Vardhan Vashistha
- 申请人： Splunk Inc.
- 申请人地址： US CA San Francisco
- 专利权人： Splunk Inc.
- 当前专利权人： Splunk Inc.
- 当前专利权人地址： US CA San Francisco
- 代理机构： Knobbe, Martens, Olson & Bear, LLP
- 主分类号： G06F16/00
- IPC分类号： G06F16/00 ; G06F16/904 ; G06F11/32 ; G06F16/9038 ; G06F16/9035
摘要：
A system can display content generated from one type of machine-generated data to a user via a graphical user interface. Based on an interaction with the machine-generated data, the system can determine an entity identifier associated with the machine-generated data and determine an entity type for the entity identifier. The system can map the entity type to one or more content generators associated with the entity type and communicate the entity identifier to the identified content generators. The content generators can determine if they have content associated with the machine-generated data. The system can generate and display a link to the related content via a graphical user interface.
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