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    Results ranking with simultaneous searchee and searcher optimization
    3.
    发明授权
    Results ranking with simultaneous searchee and searcher optimization 有权

    公开(公告)号：US11768843B1

    公开(公告)日：2023-09-26

    申请号：US17752753

    申请日：2022-05-24

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Peng Du ,  Mathew H. Teoh ,  Rupesh Gupta ,  Anand Kishore

    IPC: G06F16/2457 ,  G06F16/248

    CPC classification number: G06F16/24578 ,  G06F16/248 ,  G06F16/24573

    Abstract: Embodiments include technologies to apply at least one machine learning model to features of a search query, features of a searcher user, features of a searchee content item, and features of a searchee user, produce a first outcome prediction that represents a probability of a first objective relating to engagement of the searcher user with a content item in an online system and a second outcome prediction that represents a probability of a second objective relating to engagement of the searchee user with the online system responsive to the engagement of the searcher user with the content item, apply a multi-objective optimization solver to the first objective, the second objective and an outcome prediction that is a combination of the first outcome prediction and the second outcome prediction, and generate a serving function for a search engine based on the first objective, the second objective, and the outcome prediction.

    MACHINE LEARNING TECHNIQUES FOR MULTI-OBJECTIVE CONTENT ITEM SELECTION
    6.
    发明申请
    MACHINE LEARNING TECHNIQUES FOR MULTI-OBJECTIVE CONTENT ITEM SELECTION 审中-公开

    公开(公告)号：US20200005354A1

    公开(公告)日：2020-01-02

    申请号：US16024753

    申请日：2018-06-30

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Rupesh Gupta ,  Guangde Chen ,  Curtis Chung-Yen Wang ,  Deepak K. Agarwal ,  Souvik Ghosh ,  Shipeng Yu

    IPC: G06Q30/02 ,  G06Q10/06 ,  G06N99/00

    Abstract: Machine learning techniques for multi-objective content item selection are provided. In one technique, resource allocation data is stored that indicates, for each campaign of multiple campaigns, a resource allocation amount that is assigned by a central authority. In response to receiving the content request, a subset of the campaigns is identified based on targeting criteria. Multiple scores are generated, each score reflecting a likelihood that a content item of the corresponding campaign will be selected. Based on the scores, a particular campaign from the subset is selected and the corresponding content item transmitted over a computer network to be displayed on a computing device. A resource allocation amount that is associated with the particular campaign is identified. A resource reduction amount associated with displaying the content item of the particular campaign is determined. The particular resource allocation is reduced based on the resource reduction amount.

    Managing unprofessional media content
    7.
    发明授权
    Managing unprofessional media content 有权

    公开(公告)号：US10476824B2

    公开(公告)日：2019-11-12

    申请号：US14814563

    申请日：2015-07-31

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Rupesh Gupta ,  Mahdiehsadat Mirian Hosseinabadi

    IPC: H04L12/58

    Abstract: Systems and methods for storing less than a threshold number of media content activity levels for media content objects at an online social networking service, identifying, using the stored media content activities, a threshold number of media content objects associated with a higher number of the media content activities occurring over a recent threshold period of time, receiving an indicator indicating that one of the identified media content objects is unprofessional, and propagating the indicator to each activity that includes the unprofessional media content object.

    Active user message diet
    8.
    发明授权
    Active user message diet 有权

    公开(公告)号：US10692014B2

    公开(公告)日：2020-06-23

    申请号：US15194300

    申请日：2016-06-27

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Rupesh Gupta ,  Guanfeng Liang

    IPC: G06Q30/02 ,  G06Q10/10 ,  G06Q10/06 ,  G06Q40/02 ,  G06Q99/00 ,  G06N20/00 ,  G06Q50/00 ,  G16H40/63 ,  G16H10/60 ,  G16H50/50 ,  G16H50/20 ,  G16H20/60 ,  G06N7/00 ,  G06N5/00 ,  G06N3/08 ,  G06N20/10

    Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Message Diet Engine that generates a pool of messages for a plurality member accounts of a social network service. Each message being of a respective message type from a plurality of message types and targeted to a specific member account. For each respective member account, the Message Diet Engine selects a minimum number of messages, from the pool of messages, targeted to the respective member account that prompts an expected social network activity target and avoids an expected number of complaints. Based on the selected minimum number of messages for each respective member account, the Message Diet Engine identifies a total minimum number of messages, from the pool of messages, to be sent to the plurality of member accounts that prompts an expected total social network activity target and avoids a total expected number of complaints.

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