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公开(公告)号：US10803127B2
公开(公告)日：2020-10-13
申请号：US15601806
申请日：2017-05-22
Applicant: salesforce.com, inc.
IPC: G06F16/907 , G06F16/31 , G06F16/335 , G06F16/33 , G06N3/08 , G06N3/04 , G06F40/30
Abstract: A record management system retrieves relevance information through an information retrieval model that models relevance between users, queries, and records based on user interaction data with records. Relevance information between different elements of the record management system are determined through a set of learned transformations in the information retrieval model. The record management system can quickly retrieve relevance information between different elements of the record management system given the set of learned transformations in the information retrieval model, without the need to construct separate systems for different types of relevance information. Moreover, even without access to contents of records, the record management system can determine relevant records for a given query based on user interaction data and the determined relationships between users, queries, and records learned through the information retrieval model.
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Patent Agency Ranking
公开(公告)号：US20180096372A1
公开(公告)日：2018-04-05
申请号：US15721346
申请日：2017-09-29
Applicant: salesforce.com, inc.
Inventor： Scott Thurston Rickard, JR. , Elizabeth Rachel Balsam , Tracy Morgan Backes , Zachary Alexander
CPC classification number: G06N5/022 , G06N3/08 , G06N5/003 , G06N7/005 , G06N20/00 , G06N20/10 , G06N20/20 , G06Q30/0201 , G06Q30/0203 , G06Q30/0204
Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.
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公开(公告)号：US20180096250A1
公开(公告)日：2018-04-05
申请号：US15721336
申请日：2017-09-29
Applicant: salesforce.com, inc.
Inventor： Scott Thurston Rickard, JR. , Elizabeth Rachel Balsam , Tracy Morgan Backes , Zachary Alexander
CPC classification number: G06N5/022 , G06N3/08 , G06N5/003 , G06N7/005 , G06N20/00 , G06N20/10 , G06N20/20 , G06Q30/0201 , G06Q30/0203 , G06Q30/0204
Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.
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公开(公告)号：US11651237B2
公开(公告)日：2023-05-16
申请号：US15721346
申请日：2017-09-29
Applicant: salesforce.com, inc.
Inventor： Scott Thurston Rickard, Jr. , Elizabeth Rachel Balsam , Tracy Morgan Backes , Zachary Alexander
IPC: G06Q30/02 , G06N20/10 , G06N5/022 , G06N20/00 , G06N5/00 , G06N20/20 , G06Q30/0201 , G06Q30/0203 , G06Q30/0204 , G06N3/08 , G06N7/00
CPC classification number: G06N5/022 , G06N5/003 , G06N20/00 , G06N20/20 , G06Q30/0201 , G06Q30/0203 , G06Q30/0204 , G06N3/08 , G06N7/005 , G06N20/10
Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.
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5.发明申请公开(公告)号：US20180089585A1
公开(公告)日：2018-03-29
申请号：US15280126
申请日：2016-09-29
Applicant: salesforce.com, inc.
Inventor： Scott Thurston Rickard, Jr. , Elizabeth Rachel Balsam , Tracy Morgan Backes , Siddharth Rajaram , Zachary Alexander , Gregory Thomas Pascale
IPC: G06N99/00
CPC classification number: G06N20/00 , G06Q10/06375 , G06Q30/02
Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses machine learning techniques to predict likelihood of success for a potential transaction object. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data as training dataset for a predictor model. The online system extracts features describing potential transaction objects and provides these as input to the predictor model for predicting the likelihood of success of a given potential transaction. The online system may use predictions of likelihood of success of potential transactions to identify a set of potential transactions that should be acted upon to maximize the benefit the enterprise within a time interval, for example, by the end of the current month.
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公开(公告)号：US20170351781A1
公开(公告)日：2017-12-07
申请号：US15601806
申请日：2017-05-22
Applicant: salesforce.com, inc.
Abstract: A record management system retrieves relevance information through an information retrieval model that models relevance between users, queries, and records based on user interaction data with records. Relevance information between different elements of the record management system are determined through a set of learned transformations in the information retrieval model. The record management system can quickly retrieve relevance information between different elements of the record management system given the set of learned transformations in the information retrieval model, without the need to construct separate systems for different types of relevance information. Moreover, even without access to contents of records, the record management system can determine relevant records for a given query based on user interaction data and the determined relationships between users, queries, and records learned through the information retrieval model.
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