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1.发明授权公开(公告)号：US10528909B2
公开(公告)日：2020-01-07
申请号：US15482453
申请日：2017-04-07
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Yangli Hector Yee , Peng Ye , Fenglin Liao , Li Zhang , Kim Pham , Julian Qian , Benjamin Yolken
摘要： This disclosure includes systems for regression-tree-modified feature vector machine learning models for utilization prediction in time-expiring inventory. An online computing system receives a feature vector for a listing and inputs the feature vector and modified feature vectors into a demand function to generate demand estimates. The system inputs the demand estimates into a likelihood model to generate a set of request likelihoods, each request likelihood representing a likelihood that the time-expiring inventory will receive a transaction request at each of a set of test price and test times to expiration. The system further trains a regression tree model based on a set of training data comprising each of the request likelihoods from the set and the test price and test time period to expiration used to generate the demand estimate that was used to generate the request likelihood.
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2.发明申请公开(公告)号：US20170308846A1
公开(公告)日：2017-10-26
申请号：US15482453
申请日：2017-04-07
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Yangli Hector Yee , Peng Ye , Fenglin Liao , Li Zhang , Kim Pham , Julian Qian , Benjamin Yolken
摘要： This disclosure includes systems for regression-tree-modified feature vector machine learning models for utilization prediction in time-expiring inventory. An online computing system receives a feature vector for a listing and inputs the feature vector and modified feature vectors into a demand function to generate demand estimates. The system inputs the demand estimates into a likelihood model to generate a set of request likelihoods, each request likelihood representing a likelihood that the time-expiring inventory will receive a transaction request at each of a set of test price and test times to expiration. The system further trains a regression tree model based on a set of training data comprising each of the request likelihoods from the set and the test price and test time period to expiration used to generate the demand estimate that was used to generate the request likelihood.
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公开(公告)号：US10204144B2
公开(公告)日：2019-02-12
申请号：US14815655
申请日：2015-07-31
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Kim Pham , Maxim Charkov
摘要： A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked by a user without first requesting the operator to manually approve the transaction request and waiting for the operator's approval of the request. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfill the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.
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4.发明申请Automated Database Record Activation Using Predictive Modeling of Database Access 审中-公开使用数据库访问的预测建模自动数据库记录激活公开(公告)号：US20170031914A1
公开(公告)日：2017-02-02
申请号：US14815655
申请日：2015-07-31
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Kim Pham , Maxim Charkov
IPC分类号： G06F17/30
CPC分类号： G06F17/3053 , G06F17/30554 , G06Q10/02 , G06Q30/0205 , G06Q50/14
摘要： A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked by a user without first requesting the operator to manually approve the transaction request and waiting for the operator's approval of the request. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfil the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.
摘要翻译： 一种计算机实现的系统和方法，用于选择和通知操作者该选项以在短时间间隔内为所选择的地理区域中提供的记录启用记录激活功能。 为记录启用记录激活表示该记录可以由用户预订，而不首先要求操作者手动批准交易请求并等待运营商对该请求的批准。 在选择和通知运营商之前，预测了对数据库请求的需求。 确定最有可能提供记录激活记录的运算符。 基于记录在编程启用记录激活之后记录将被预约的可能性，确定每个已识别记录的质量得分。 根据其质量得分选择满足数据库请求需求的记录，并通知所选记录的运算符以启用记录激活的选项。
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公开(公告)号：US10942931B2
公开(公告)日：2021-03-09
申请号：US16235551
申请日：2018-12-28
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Kim Pham , Maxim Charkov
IPC分类号： G06F16/2457 , G06Q30/02 , G06Q50/14 , G06F16/248 , G06Q10/02
摘要： A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked without the operator's to manual approval of the transaction. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfill the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.
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6.发明申请公开(公告)号：US20200090116A1
公开(公告)日：2020-03-19
申请号：US16688569
申请日：2019-11-19
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Yangli Hector Yee , Peng Ye , Fenglin Liao , Li Zhang , Kim Pham , Julian Qian , Benjamin Yolken
摘要： This disclosure includes systems for regression-tree-modified feature vector machine learning models for utilization prediction in time-expiring inventory. An online computing system receives a feature vector for a listing and inputs the feature vector and modified feature vectors into a demand function to generate demand estimates. The system inputs the demand estimates into a likelihood model to generate a set of request likelihoods, each request likelihood representing a likelihood that the time-expiring inventory will receive a transaction request at each of a set of test price and test times to expiration. The system further trains a regression tree model based on a set of training data comprising each of the request likelihoods from the set and the test price and test time period to expiration used to generate the demand estimate that was used to generate the request likelihood.
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公开(公告)号：US20190138529A1
公开(公告)日：2019-05-09
申请号：US16235551
申请日：2018-12-28
申请人： Airbnb, Inc.
发明人： Spencer de Mars , Kim Pham , Maxim Charkov
IPC分类号： G06F16/2457 , G06F16/248 , G06Q50/14 , G06Q30/02 , G06Q10/02
摘要： A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked without the operator's to manual approval of the transaction. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfill the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.
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