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公开(公告)号：US20200007634A1
公开(公告)日：2020-01-02
申请号：US16023230
申请日：2018-06-29
Applicant: Microsoft Technology Licensing, LLC
Inventor： Wanyan Xie , Shen Huang , Xiaonan Duan , Viktoras Truchanovicius , Suhai Liu
Abstract: A historical online user behavior-based approach is used to make a recommendation of a cross-online service vertical entity for a primary online service vertical entity with which a user is currently interacting online. The recommendation is made based on the similarity of historical online user behavior between the vertical entities. To do this, historical online user behavior of each of the vertical entities is represented as a respective vector. Each dimension of a vector represents a historical level of interaction between a separate user or a separate group of related users and the vertical entity represented by the vector. A similarity measure is used to measure the similarity between the vectors for the vertical entities. The recommendation of the cross-online service vertical entity is then made for the primary online service vertical entity based on the extent of the similarity between the vectors according to a similarity measure.
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公开(公告)号：US20200005244A1
公开(公告)日：2020-01-02
申请号：US16022492
申请日：2018-06-28
Applicant: Microsoft Technology Licensing, LLC
Inventor： Shen Huang , Quan Wang , Huan Hoang , Yongzheng Zhang , Chi-Yi Kuan
Abstract: Techniques for discovering related organizations through different types of online connections are provided. In one technique, connection data is stored that identifies, for each user in a first set of users, one or more other users with which that user has a connection. Job change data is stored that identifies, for each user of a second set of users, multiple organizations for which that user has worked or had sought an employment relationship. Based on the connection data, a number of connections between employees of a first organization and employees of a second organization is identified. Based on the job change data, a number of users that listed, in their respective online profiles, the first organization as an employer is identified. Based on the number of connections and the number of users, a determination of whether the first organization and the second organization are related is made.
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公开(公告)号：US20190303773A1
公开(公告)日：2019-10-03
申请号：US15941236
申请日：2018-03-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chi-Yi Kuan , Shen Huang , Yu Wang , Yongzheng Zhang , Paul Ko , Shady Elasra , Fanbin Bu
Abstract: Techniques are provided for predicting talent flow to and/or from a geographical region. In one technique, multiple entity profiles are stored and analyzed to generate training data that is labeled indicating whether a corresponding entity has moved to or moved from a region. A machine-learned prediction model is generated or trained based on the training data. Using the machine-learned prediction model, a prediction is made whether, for each entity corresponding to another entity profile, that entity will move to or move from a particular geographic region. Based on multiple predictions, a number of entities that are predicted to move to or move from the particular geographic region is determined. Talent flow data that is based on the number of entities is presented on a computer display.
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公开(公告)号：US20190197479A1
公开(公告)日：2019-06-27
申请号：US15853658
申请日：2017-12-22
Applicant: Microsoft Technology Licensing, LLC
Inventor： Shen Huang , Yongzheng Zhang , Chi-Yi Kuan
CPC classification number: G06Q10/107 , G06F21/55 , G06F21/62 , H04L51/046 , H04L51/12 , H04L51/18 , H04L51/32 , H04L51/34 , H04L63/0227 , H04W4/14
Abstract: Techniques for delaying the transmission of a message to one or more recipients using an alert in order to provide data protection and security with respect to data included in the message are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a request to transmit a message from a computing device of a user to a recipient, the request comprising content of the message; detecting an issue with the request using at least one classifier to classify the request as having the issue; generating an alert based on the detecting of the issue; and prior to transmitting the message to a destination associated with the recipient, causing the generated alert to be displayed on the computing device of the user, the alert indicating the issue with the message.
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公开(公告)号：US11074521B2
公开(公告)日：2021-07-27
申请号：US15941280
申请日：2018-03-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Wanyan Xie , Yue Li , Eric Weber , Yanjin Kuang , Shen Huang
Abstract: In an example embodiment, profile and/or usage data of a social networking service is leveraged to automatically generate potential career paths for users of the social networking service. Additionally, specific recommendations as to actions the users can take to increase their odds of progressing along particular career paths can be determined, and these recommendations can be shared with users. Both recommendations may be performed in a manner that is scalable for personalized service.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20200342351A1
公开(公告)日：2020-10-29
申请号：US16397686
申请日：2019-04-29
Applicant: Microsoft Technology Licensing, LLC
Inventor： Suhai Liu , Haowen Cao , Shen Huang
Abstract: Techniques for using machine learning techniques to distinguish between different types of uses of an online service are provided. In one technique, first training data is used to train a first prediction model and second training data is used to train a second prediction model. The label of training instances in the first training data indicates whether an online action with respect to an online service of one type of action or another type of action. The label of training instances in the second training data indicates whether an entity using the online service initiated a particular action. The first prediction model is used to classify multiple actions performed by an entity relative to the online service. The second prediction model takes the classifications produced by the first prediction model to determine a likelihood that the entity will initiate the particular action.
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公开(公告)号：US11457074B2
公开(公告)日：2022-09-27
申请号：US16370690
申请日：2019-03-29
Applicant: Microsoft Technology Licensing, LLC
Inventor： Kaiyu Yang , Li Yang , Yongzheng Zhang , Shen Huang , Clayton Sanford
IPC: H04L67/30 , G06N20/00 , H04L67/10 , H04L47/70 , G09B5/00 , G09B5/06 , G06Q50/00 , G09B5/02 , G09B5/04
Abstract: An embodiment of the disclosed technologies includes extracting, from an online connection network, digital data comprising target profile data and current profile data; where the target profile data is associated with an online submission process that has a plurality of possible outcomes and is executable via the online connection network; where the current profile data is associated with a member node of the online connection network; using an active learning process, in response to the current profile data, identifying attribute data that is in the target profile data but is not in the current profile data and is predicted to have a relationship with a positive outcome of the online submission process; outputting the attribute data for use by a downstream process or an automated digital assistant to determine a digital resource to associate with the member node through the online connection network or through an online learning system.
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公开(公告)号：US11238352B2
公开(公告)日：2022-02-01
申请号：US15941236
申请日：2018-03-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chi-Yi Kuan , Shen Huang , Yu Wang , Yongzheng Zhang , Paul Ko , Shady Elasra , Fanbin Bu
Abstract: Techniques are provided for predicting talent flow to and/or from a geographical region. In one technique, multiple entity profiles are stored and analyzed to generate training data that is labeled indicating whether a corresponding entity has moved to or moved from a region. A machine-learned prediction model is generated or trained based on the training data. Using the machine-learned prediction model, a prediction is made whether, for each entity corresponding to another entity profile, that entity will move to or move from a particular geographic region. Based on multiple predictions, a number of entities that are predicted to move to or move from the particular geographic region is determined. Talent flow data that is based on the number of entities is presented on a computer display.
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公开(公告)号：US10733572B2
公开(公告)日：2020-08-04
申请号：US15853658
申请日：2017-12-22
Applicant: Microsoft Technology Licensing, LLC
Inventor： Shen Huang , Yongzheng Zhang , Chi-Yi Kuan
Abstract: Techniques for delaying the transmission of a message to one or more recipients using an alert in order to provide data protection and security with respect to data included in the message are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a request to transmit a message from a computing device of a user to a recipient, the request comprising content of the message; detecting an issue with the request using at least one classifier to classify the request as having the issue; generating an alert based on the detecting of the issue; and prior to transmitting the message to a destination associated with the recipient, causing the generated alert to be displayed on the computing device of the user, the alert indicating the issue with the message.
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公开(公告)号：US20200210390A1
公开(公告)日：2020-07-02
申请号：US16237137
申请日：2018-12-31
Applicant: Microsoft Technology Licensing, LLC
Inventor： Shen Huang , Huan Van Hoang , Yongzheng Zhang , Chi-Yi Kuan
IPC: G06F16/215 , G06N20/00 , G06F16/28 , G06Q10/10
Abstract: Methods, systems, and computer programs are presented for selecting features for a machine-learning model configured to detect anomalies in the evolution of data over time. One method includes an operation for identifying one or more key fields and value fields from the fields in a relational database. The method also includes grouping data of the value fields based on values of the one or more key fields and calculating one or more statistical values for each group of data of the value fields. The method further includes operations for monitoring an evolution of the one or more statistical values over time, and for selecting, based on the evolution of the one or more statistical values over time, features to be used by a machine-learning model to detect anomalies in content of the relational database over time. The method also includes executing the machine-learning model to detect the anomalies.
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