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公开(公告)号：US20190303877A1
公开(公告)日：2019-10-03
申请号：US15941501
申请日：2018-03-30
发明人： Benjamin John McCann , Jerry Lin , Erik Eugene Buchanan , Alexis Blevins Baird , Skylar Payne , Nadeem Anjum
摘要： Systems and methods for analyzing pipelined data are disclosed. In some examples, a server receives a transaction description requesting candidates for a given transaction. The server accesses first records representing parties that fully completed the given transaction and second records representing parties that were in a pipeline for completing the given transaction but did not fully complete the given transaction. The first records and the second records are stored at a data repository. The server generates a model for predicting whether an identified record represents a party likely to complete the given transaction. The model is generated based on at least the first records and the second records. The server orders a list of third records representing parties likely to complete the given transaction. The server provides an output representing the third records.
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公开(公告)号：US20190197192A1
公开(公告)日：2019-06-27
申请号：US15942375
申请日：2018-03-30
CPC分类号： G06Q10/1053 , G06F16/1834 , G06F16/24578 , G06F16/285 , G06F16/635 , G06F16/735 , G06F16/9032 , G06F16/90324 , G06F16/9535 , G06N7/005 , G06N20/00 , G06Q10/063112 , G06Q50/01
摘要： An example system generates a search query for candidates, the search query comprising a set of parameters corresponding to attributes extracted from one or more stream-related information sources, each parameter in the set having a weight. Additionally, the system executes the query on member profiles of members of an online system to return search results based on the parameters and the weights of the parameters. Moreover, the system causes presentation of at least one search result from the search results, the at least one search result, being associated with at least one of the attributes. Furthermore, the system accesses feedback to the at least one search result that indicates a level of interest in the search result. Then, the system adjusts the parameters based on the feedback. Next, the system causes presentation of an updated search result, the updated search result being generated based on the adjusted set of parameters.
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公开(公告)号：US20190164096A1
公开(公告)日：2019-05-30
申请号：US15827289
申请日：2017-11-30
发明人： Gio Borje , Benjamin John McCann , David DiCato , Jerry Lin , Skylar Payne , Apoorv Khandelwal , Nadeem Anjum
摘要： Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.
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公开(公告)号：US11429915B2
公开(公告)日：2022-08-30
申请号：US15827289
申请日：2017-11-30
发明人： Gio Borje , Benjamin John McCann , David DiCato , Jerry Lin , Skylar Payne , Apoorv Khandelwal , Nadeem Anjum
摘要： Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.
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公开(公告)号：US10423676B1
公开(公告)日：2019-09-24
申请号：US15341711
申请日：2016-11-02
IPC分类号： G06F16/248 , H04L29/08 , G06F21/60 , G06F16/951 , G06F16/955
摘要： Systems and methods for identifying user information from a set of pages are disclosed. In example embodiments, a server determines that a first set of pages is associated with a specific user based on addresses of the first set of pages having a common portion of a uniform resource locator (URL). The server determines that at least a threshold number of pages from the first set of pages include common information, the common information comprising contact information or social networking information. The server associates the contact information or the social networking information with a user profile of the specific user. The server provides, as a digital transmission, the contact information or the social networking information.
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公开(公告)号：US20190188273A1
公开(公告)日：2019-06-20
申请号：US15845477
申请日：2017-12-18
IPC分类号： G06F17/30
CPC分类号： G06F16/24578 , G06F16/248 , G06F16/3334
摘要： Systems and methods for query term weighting are disclosed. A server receives a search query for employment candidates, the search query comprising a set of parameters, each parameter having a weight. The server generates, from a data repository storing records associated with professionals, a first set of search results based on the set of parameters and the weights of the parameters in the set. The server transmits the first set of search results. The server receives a response to search result(s) from the first set of search results, the search result(s) being associated with a set of factors, the response indicating a level of interest in the search result(s). The server adjusts the parameters in the set of parameters or adjusts the weights of the parameters based on the response to the search result(s). The server provides an output based on the adjusted parameters or the adjusted weights.
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公开(公告)号：US20190163668A1
公开(公告)日：2019-05-30
申请号：US15827329
申请日：2017-11-30
发明人： Gio Borje , Benjamin John McCann , David DiCato , Jerry Lin , Skylar Payne , Apoorv Khandelwal , Nadeem Anjum
摘要： Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.
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公开(公告)号：US11010688B2
公开(公告)日：2021-05-18
申请号：US15827329
申请日：2017-11-30
发明人： Gio Borje , Benjamin John McCann , David DiCato , Jerry Lin , Skylar Payne , Apoorv Khandelwal , Nadeem Anjum
IPC分类号： G06F17/16 , G06N20/00 , G06Q10/06 , G06F17/15 , G06Q10/10 , G06K9/00 , G06F17/18 , G06N20/10
摘要： Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.
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公开(公告)号：US10740339B2
公开(公告)日：2020-08-11
申请号：US15845477
申请日：2017-12-18
IPC分类号： G06F16/33 , G06F16/2457 , G06F16/248
摘要： Systems and methods for query term weighting are disclosed. A server receives a search query for employment candidates, the search query comprising a set of parameters, each parameter having a weight. The server generates, from a data repository storing records associated with professionals, a first set of search results based on the set of parameters and the weights of the parameters in the set. The server transmits the first set of search results. The server receives a response to search result(s) from the first set of search results, the search result(s) being associated with a set of factors, the response indicating a level of interest in the search result(s). The server adjusts the parameters in the set of parameters or adjusts the weights of the parameters based on the response to the search result(s). The server provides an output based on the adjusted parameters or the adjusted weights.
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公开(公告)号：US10521489B2
公开(公告)日：2019-12-31
申请号：US15827350
申请日：2017-11-30
发明人： Gio Borje , Benjamin John McCann , David DiCato , Jerry Lin , Skylar Payne , Apoorv Khandelwal , Nadeem Anjum
摘要： Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.
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