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公开(公告)号：US10116759B2
公开(公告)日：2018-10-30
申请号：US14948993
申请日：2015-11-23
Applicant: Huawei Technologies Co., Ltd.
Inventor： Wei Fan , Jianfeng Qian , Yadong Mu
Abstract: A method and an apparatus for identifying a state of a user of a social network. The identification method includes acquiring a user-event similarity of a user regarding a new event; identifying whether the user is a silent user or a non-activated user according to the user-event similarity; and determining whether the silent user or the non-activated user on the social network is finally in an activated state or a non-activated state. In the foregoing manner, a novel user state model of a social network is designed in the present disclosure, the model includes an activated state, a non-activated state and an unstable silent state, and a final state of a user is inferred precisely under full and comprehensive consideration of factors that may affect the state of the user, such that the state of the user can be accurately and precisely monitored.
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2.发明申请Method, Apparatus and Computer for Identifying State of User of Social Network 审中-公开用于识别社交网络用户状态的方法，设备和计算机公开(公告)号：US20160088105A1
公开(公告)日：2016-03-24
申请号：US14948993
申请日：2015-11-23
Applicant: Huawei Technologies Co., Ltd.
Inventor： Wei Fan , Jianfeng Qian , Yadong Mu
Abstract: A method and an apparatus for identifying a state of a user of a social network. The identification method includes acquiring a user-event similarity of a user regarding a new event; identifying whether the user is a silent user or a non-activated user according to the user-event similarity; and determining whether the silent user or the non-activated user on the social network is finally in an activated state or a non-activated state. In the foregoing manner, a novel user state model of a social network is designed in the present disclosure, the model includes an activated state, a non-activated state and an unstable silent state, and a final state of a user is inferred precisely under full and comprehensive consideration of factors that may affect the state of the user, such that the state of the user can be accurately and precisely monitored.
Abstract translation: 一种用于识别社交网络的用户的状态的方法和装置。 识别方法包括获取用户关于新事件的用户事件相似性; 根据所述用户事件相似性来识别所述用户是静默用户还是非激活用户; 以及确定所述社交网络上的无声用户或未激活的用户是否处于激活状态或非激活状态。 以上述方式，在本公开中设计了社交网络的新型用户状态模型，该模型包括激活状态，非激活状态和不稳定静音状态，并且精确地推断用户的最终状态 充分和全面地考虑可能影响用户状态的因素，使得用户的状态可以被准确和精确地监视。
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3.发明授权公开(公告)号：US09755616B2
公开(公告)日：2017-09-05
申请号：US15391122
申请日：2016-12-27
Applicant: Huawei Technologies Co., Ltd.
CPC classification number: H03H17/0248 , G06F17/30997
Abstract: A method for data filtering includes segmenting a to-be-detected vector to obtain k to-be-detected sub-vectors, respectively performing an inner product operation on the k to-be-detected sub-vectors and corresponding detection vectors among preset k detection vectors to obtain k first operation results, determining a first operation result whose value is the maximum among the k first operation results and obtaining an identifier of a detection vector corresponding to the first operation result, where a detection vector is in a one-to-one correspondence to an identifier, and mapping the to-be-detected vector to a preset data filter according to the obtained identifier of the detection vector corresponding to the first operation result whose value is the maximum, and determining, using the data filter, whether to filter out the to-be-detected vector.
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4.发明申请公开(公告)号：US20170111030A1
公开(公告)日：2017-04-20
申请号：US15391122
申请日：2016-12-27
Applicant: Huawei Technologies Co., Ltd.
IPC: H03H17/02
CPC classification number: H03H17/0248 , G06F17/30997
Abstract: A method for data filtering includes segmenting a to-be-detected vector to obtain k to-be-detected sub-vectors, respectively performing an inner product operation on the k to-be-detected sub-vectors and corresponding detection vectors among preset k detection vectors to obtain k first operation results, determining a first operation result whose value is the maximum among the k first operation results and obtaining an identifier of a detection vector corresponding to the first operation result, where a detection vector is in a one-to-one correspondence to an identifier, and mapping the to-be-detected vector to a preset data filter according to the obtained identifier of the detection vector corresponding to the first operation result whose value is the maximum, and determining, using the data filter, whether to filter out the to-be-detected vector.
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