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1.发明授权公开(公告)号：US12106187B2
公开(公告)日：2024-10-01
申请号：US16940713
申请日：2020-07-28
发明人： Carlos E. Hernández Rincón , Andrew Richard Rundell , Terence Joseph Munday , James Edward Bridges, Jr. , Mariana Dayanara Alanis Tamez , Josue Emmanuel Gomez Carrillo
IPC分类号： G06N20/00 , G06F16/215 , G06F16/25
CPC分类号： G06N20/00 , G06F16/215 , G06F16/254
摘要： Systems and method are provided for data flattening. A corpus of data is extracted from at least one data source and stored at a data warehousing platform. A workflow is applied to the extracted corpus of data to provide a transformed corpus of data. The workflow includes a sequence of atomic functions selected from a library of atomic functions to perform an associated task on the corpus of data. The transformed corpus of data is provided from the data warehousing platform to a machine learning model as a set of training data.
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公开(公告)号：US11386366B2
公开(公告)日：2022-07-12
申请号：US16940743
申请日：2020-07-28
IPC分类号： G06Q10/06 , G06F16/2457 , G06N20/00
摘要： A system and method are presented for cold start candidate recommendation. In some examples, a search query request that includes a candidate search parameter can be received for a candidate list. During a first search query, a subset of candidates from a plurality of candidates can be identified based on a comparison of each candidate vector for each candidate and a candidate search parameter vector for the candidate search parameter, and ranked to provide an initial ranked candidate list based on assigned scores for the subset of candidates. During a second search query, the search parameter a candidate index can be evaluated to identify a set of candidates from the plurality of candidates, re-ranked to provide an updated ranked candidate list corresponding to the candidate list based on updated assigned scores for the set candidates and a re-ranking parameter.
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3.发明申请公开(公告)号：US20210081838A1
公开(公告)日：2021-03-18
申请号：US16940713
申请日：2020-07-28
发明人： Carlos E. Hernández Rincón , Andrew Richard Rundell , Terence Joseph Munday , James Edward Bridges, JR. , Mariana Dayanara Alanis Tamez , Josue Emmanuel Gomez Carrillo
IPC分类号： G06N20/00 , G06F16/25 , G06F16/215
摘要： Systems and method are provided for data flattening. A corpus of data is extracted from at least one data source and stored at a data warehousing platform. A workflow is applied to the extracted corpus of data to provide a transformed corpus of data. The workflow includes a sequence of atomic functions selected from a library of atomic functions to perform an associated task on the corpus of data. The transformed corpus of data is provided from the data warehousing platform to a machine learning model as a set of training data
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