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23 条记录 (耗时 0.017 秒)

    Identifying user information from a set of pages
    1.
    发明授权
    Identifying user information from a set of pages 有权

    公开(公告)号：US10423676B1

    公开(公告)日：2019-09-24

    申请号：US15341711

    申请日：2016-11-02

    申请人： Microsoft Technology Licensing, LLC

    发明人： John Robert Jersin ,  Benjamin John McCann ,  Erik Eugene Buchanan ,  Gio Borje

    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.

    QUERY TERM WEIGHTING
    2.
    发明申请
    QUERY TERM WEIGHTING 审中-公开

    公开(公告)号：US20190188273A1

    公开(公告)日：2019-06-20

    申请号：US15845477

    申请日：2017-12-18

    申请人： Microsoft Technology Licensing, LLC

    发明人： Nadeem Anjum ,  Skylar Payne ,  Jerry Lin ,  Benjamin John McCann ,  Erik Eugene Buchanan

    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.

    Standardized entity representation learning for smart suggestions
    3.
    发明授权
    Standardized entity representation learning for smart suggestions 有权

    公开(公告)号：US10726025B2

    公开(公告)日：2020-07-28

    申请号：US15898964

    申请日：2018-02-19

    申请人： Microsoft Technology Licensing, LLC

    发明人： Qi Guo ,  Xianren Wu ,  Bo Hu ,  Shan Zhou ,  Lei Ni ,  Erik Eugene Buchanan

    IPC分类号： G06F16/00 ,  G06F16/2457 ,  G06N20/00 ,  G06F16/248 ,  G06F16/901 ,  H04L29/06 ,  H04L29/08

    摘要： In an example, a plurality of user profiles in a social networking service are accessed. A heterogeneous graph structure having a plurality of nodes connected by edges is generated, each node corresponding to a different entity in the social networking service, each edge representing a co-occurrence of entities represented by nodes on each side of the edge in at least one of the user profiles. Weights are calculated for each edge of the heterogeneous graph structure, the weights being based on co-occurrence counts reflecting a number of user profiles in the plurality of user profiles in which corresponding nodes co-occurred. The heterogeneous graph structure is embedded into a d-dimensional space. A machine-learned model is then used to calculate a similarity score between a first node and second node by computing distance between the first node and the second node in the d¬-dimensional space.

    ANALYZING PIPELINED DATA
    4.
    发明申请
    ANALYZING PIPELINED DATA 审中-公开

    公开(公告)号：US20190303877A1

    公开(公告)日：2019-10-03

    申请号：US15941501

    申请日：2018-03-30

    申请人： Microsoft Technology Licensing, LLC

    发明人： Benjamin John McCann ,  Jerry Lin ,  Erik Eugene Buchanan ,  Alexis Blevins Baird ,  Skylar Payne ,  Nadeem Anjum

    IPC分类号： G06Q10/10 ,  G06Q10/06

    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.

    Smart suggestions personalization with GLMix
    6.
    发明授权
    Smart suggestions personalization with GLMix 有权

    公开(公告)号：US10956515B2

    公开(公告)日：2021-03-23

    申请号：US15898976

    申请日：2018-02-19

    申请人： Microsoft Technology Licensing, LLC

    发明人： Qi Guo ,  Xianren Wu ,  Bo Hu ,  Shan Zhou ,  Lei Ni ,  Erik Eugene Buchanan

    IPC分类号： G06F16/90 ,  G06F16/951 ,  G06Q50/00 ,  G06N20/00

    摘要： In an example, an indication of a plurality of different entities in a social networking service is received, including at least two entities having a different entity type. Then a plurality of user profiles in the social networking service are accessed. A machine-learned model is then used to calculate, based on co-occurrence counts reflecting a number of user profiles in the plurality of user profiles in which corresponding nodes co-occurred, a similarity score between a first node and second node by computing distance between the first node and the second node in a d-dimensional space on which a plurality of entities are mapped, the similarity score generated using a generalized linear mixed model having a global coefficient vector applied to global function pertaining to the co-occurrence counts and a first random effects coefficient vector applied to a random effects per-country function.

    Query term weighting
    7.
    发明授权
    Query term weighting 有权

    公开(公告)号：US10740339B2

    公开(公告)日：2020-08-11

    申请号：US15845477

    申请日：2017-12-18

    申请人： Microsoft Technology Licensing, LLC

    发明人： Nadeem Anjum ,  Skylar Payne ,  Jerry Lin ,  Benjamin John McCann ,  Erik Eugene Buchanan

    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.

    STANDARDIZED ENTITY REPRESENTATION LEARNING FOR SMART SUGGESTIONS
    9.
    发明申请
    STANDARDIZED ENTITY REPRESENTATION LEARNING FOR SMART SUGGESTIONS 审中-公开

    公开(公告)号：US20190258721A1

    公开(公告)日：2019-08-22

    申请号：US15898964

    申请日：2018-02-19

    申请人： Microsoft Technology Licensing, LLC

    发明人： Qi Guo ,  Xianren Wu ,  Bo Hu ,  Shan Zhou ,  Lei Ni ,  Erik Eugene Buchanan

    IPC分类号： G06F17/30 ,  G06N99/00

    摘要： In an example, a plurality of user profiles in a social networking service are accessed. A heterogeneous graph structure comprising a plurality of nodes connected by edges is generated, each node corresponding to a different entity in the social networking service, each edge representing a co-occurrence of entities represented by nodes on each side of the edge in at least one of the user profiles. Weights are calculated for each edge of the heterogeneous graph structure, the weights being based on co-occurrence counts reflecting a number of user profiles in the plurality of user profiles in which corresponding nodes co-occurred. The heterogeneous graph structure is embedded into a d-dimensional space. A machine-learned model is then used to calculate a similarity score between a first node and second node by computing distance between the first node and the second node in the d-dimensional space.