- 专利标题: Techniques for processing queries relating to task-completion times or cross-data-structure interactions
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申请号: US15592949申请日: 2017-05-11
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公开(公告)号: US09811438B1公开(公告)日: 2017-11-07
- 发明人: Ryan Barrett , Katsuya Noguchi , Nishant Bhat , Zhengua Li , Kurt Smith
- 申请人: Ryan Barrett , Katsuya Noguchi , Nishant Bhat , Zhengua Li , Kurt Smith
- 申请人地址: US CA Burlingame
- 专利权人: COLOR GENOMICS, INC.
- 当前专利权人: COLOR GENOMICS, INC.
- 当前专利权人地址: US CA Burlingame
- 代理机构: Kilpatrick Townsend & Stockton LLP
- 主分类号: G06F9/46
- IPC分类号: G06F9/46 ; G06F11/34 ; G06F9/48 ; G06N99/00 ; G06F11/30
摘要:
Methods and systems disclosed herein relate generally to data processing by applying machine learning techniques to iteration data to identify anomaly subsets of iteration data. More specifically, iteration data for individual iterations of a workflow involving a set of tasks may contain a client data set, client-associated sparse indicators and their classifications, and a set of processing times for the set of tasks performed in that iteration of the workflow. These individual iterations of the workflow may also be associated with particular data sources. Using the iteration data, anomaly subsets within the iteration data can be identified, such as data items resulting from systematic error associated with particular data sources, sets of sparse indicators to be validated or double-checked, or tasks that are associated with long processing times. The anomaly subsets can be provided in a generated communication or report in order to optimize future iterations of the workflow.