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公开(公告)号:US20180101521A1
公开(公告)日:2018-04-12
申请号:US15840482
申请日:2017-12-13
Applicant: salesforce.com, inc.
Inventor: Michael Jones , Scott Enman , Collin Chun-Kit Lee , David Campbell , Christopher John Nicholls
CPC classification number: G06F17/2785 , G06F17/218 , G06F17/24 , G06Q50/01
Abstract: Provided are techniques for avoiding sentiment model overfitting in a machine language model. A current list of keywords in a current sentiment model can be updated to create a proposed list of keywords in a proposed sentiment model. Machine-generated sentiment results, based on the proposed sentiment model, are presented to identify model overfitting, without revising the current set of keywords. The proposed set of keywords can be edited, and when overfitting is not present, the current list of keywords is replaced by the proposed list of keywords.
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公开(公告)号:US09881000B1
公开(公告)日:2018-01-30
申请号:US15213158
申请日:2016-07-18
Applicant: SALESFORCE.COM, INC.
Inventor: Michael Jones , Scott Enman , Collin Chun-Kit Lee , David Campbell , Christopher John Nicholls
CPC classification number: G06F17/2785 , G06F17/218 , G06F17/24 , G06Q50/01
Abstract: Provided are techniques for avoiding sentiment model overfitting in a machine language model. A current list of keywords in a current sentiment model can be updated to create a proposed list of keywords in a proposed sentiment model. Machine-generated sentiment results, based on the proposed sentiment model, are presented to identify model overfitting, without revising the current set of keywords. The proposed set of keywords can be edited, and when overfitting is not present, the current list of keywords is replaced by the proposed list of keywords.
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