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公开(公告)号：US20190333162A1
公开(公告)日：2019-10-31
申请号：US15966583
申请日：2018-04-30
发明人： Yijie Wang , Souvik Ghosh , Timothy Paul Jurka , Shaunak Chatterjee , Wei Xue , Bonnie Barrilleaux
IPC分类号： G06Q50/00 , G06F17/30 , G06F3/0482 , G06F15/18 , G06F17/18
摘要： A plurality of potential feed objects and corresponding identifications of actors who performed a user interface action that caused a corresponding potential feed object to be generated are obtained. The plurality of potential feed objects and corresponding actor identifications are then fed into a machine learned feed object ranking model, with the machine learned feed object ranking model having been trained via a machine learning algorithm to calculate a score for each of the potential feed objects. The score is based on a combination of a likelihood that the user will perform an interaction, via the user interface, on the potential feed object, likelihood that the user's interaction will cause one or more downstream events by other users, and likelihood that a response from a viewer will cause the actor corresponding to the potential feed object to perform an additional user interface action to generate another potential feed object.
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公开(公告)号：US20190325085A1
公开(公告)日：2019-10-24
申请号：US15959005
申请日：2018-04-20
发明人： David J. Stein , Paul T. Ogilvie , Bee-Chung Chen , Shaunak Chatterjee , Priyanka Gariba , Ke Wu , Grace W. Tang , Yangchun Luo , Boyi Chen , Amit Yadav , Ruoyang Wang , Divya Gadde , Wenxuan Gao , Amit Chandak , Varnit Agnihotri , Wei Zhuang , Joel D. Young , Weidong Zhang
摘要： The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature configuration for a feature. Next, the system obtains, from the feature configuration, an anchor containing metadata for accessing the feature in an environment. The system then uses one or more attributes of the anchor to retrieve one or more feature values of the feature from the environment. Finally, the system provides the one or more feature values for use with one or more machine-learning models.
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公开(公告)号：US10440144B2
公开(公告)日：2019-10-08
申请号：US15826462
申请日：2017-11-29
发明人： Pingjie Xiao , Shaunak Chatterjee , Shipeng Yu , Ankit Gupta , Swapnil Ghike , Vivek Nelamangala , Banu Muthukumar , Curtis Wang , Parinkumar Shah , Eric Brownrout , Changji Shi
摘要： A notification platform for distribution of notification content in an on-line social network system, on-line and in near real time, is described. As a new notification is detected in the continuous stream of notifications triggered by time-sensitive events, the near real time notifications distribution system determines member profiles representing potential recipients of the notification by traversing a relationship graph. The relationship graph has nodes representing member profiles, as well as other entities maintained in the on-line social network system. The edges of the relationship graph represent relationships between entities represented by the associated nodes. For each member profile representing a potential recipient of the notification, the near real time notifications distribution system generates a relevance score, which is used to determine whether the notification is to be delivered to the potential recipient.
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公开(公告)号：US20190190877A1
公开(公告)日：2019-06-20
申请号：US15849541
申请日：2017-12-20
发明人： Jinyun Yan , Yan Gao , Viral Gupta , Shaunak Chatterjee , Shipeng Yu , Romer E. Rosales-Delmoral , Gaurav Chandalia
CPC分类号： H04L51/32 , G06F16/9535 , H04L67/02 , H04L67/306
摘要： Techniques for reducing delay in broadcasting content over a network using an inverted fan-out process are disclosed herein. In some embodiments, a computer-implemented method comprises: in response to an activity associated with content being performed by a user on an online service, detecting that the activity has been performed: identifying a plurality of recipient users in response to the detecting; and for each one of the plurality of recipient users, transmitting a notification of the activity to a destination associated with the recipient user in response to the identifying of the recipient users, the notification comprising an indication of the content, and the transmitting of the notification of the activity being performed without waiting for the recipient user to navigate to a web page of the online service on a computing device or for the recipient to open a mobile application of the online service on a mobile device.
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公开(公告)号：US20190108209A1
公开(公告)日：2019-04-11
申请号：US15825657
申请日：2017-11-29
发明人： Karan Ashok Ahuja , Befekadu Ayenew Ejigou , Ningfeng Liang , Lokesh P. Bajaj , Wei Wang , Paul Fletcher , Wei Lu , Shaunak Chatterjee , Souvik Ghosh , Yang Li , Wei Deng , Qiang Wu
摘要： In an example, first and second machine learned models corresponding to a particular context of a social networking service are obtained, the first machine learned model trained via a first machine learning algorithm to output an indication of importance of a social networking profile field to obtaining results in the particular context, and the second machine learned model trained via a second machine learning algorithm to output a propensity of the user to edit a social networking profile field if requested. One or more missing fields in a social networking profile for the user are identified. For each of one or more of the one or more missing fields, the field and an identification of the user are passed through the first and second machine learned models, and outputs of the first and second machine learned models are combined to identify one or more top missing profile fields.
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公开(公告)号：US11968165B1
公开(公告)日：2024-04-23
申请号：US18086138
申请日：2022-12-21
摘要： Methods, systems, and computer programs are presented for selecting notifications based on an affinity score between a content generator and a viewer of the content. One method includes capturing interactions of content generators with notifications, received by the content generators, associated with viewer responses to creator-generated content items. The method further includes training a machine-learning model based on the interactions, and detecting a first set of notifications, for a first content generator, associated with interactions of a set of viewers to first-content generator content. The ML model calculates an affinity score between the first content generator and each viewer, and the set of first notifications are ranked based on the affinity scores of the first content generator and the viewer associated with each notification. A set of second notifications is selected based on the ranked first notifications; and generating notifications are generated, for the first content generator, for the selected set of second notifications.
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公开(公告)号：US20210342740A1
公开(公告)日：2021-11-04
申请号：US16866059
申请日：2020-05-04
发明人： Zhiyuan Xu , Jinyun Yan , Ajith Muralidharan , Wensheng Sun , Jiaqi Ge , Shaunak Chatterjee
IPC分类号： G06N20/00 , G06F16/9535 , G06N7/00
摘要： Techniques for selectively transmitting electronic notifications using machine learning techniques based on entity selection history are provided. In one technique, a candidate notification is identified for a target entity. An entity selection rate of the candidate notification by the target entity is determined. Based on the candidate notification, determining a probability of the target entity visiting a target online system. Based on online history of the target entity, a measure of downstream interaction by the target entity relative to one or more online systems is determined. Based on the entity selection rate, the probability, and the measure of downstream interaction by the target entity, a score for the candidate notification is generated. Based on the score, it is determined whether data about the candidate notification is to be transmitted over a computer network to a computing device of the target entity.
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公开(公告)号：US20210233119A1
公开(公告)日：2021-07-29
申请号：US16774090
申请日：2020-01-28
发明人： Zhiyuan Xu , Jinyun Yan , Shaunak Chatterjee
摘要： Techniques for using a machine-learned model to personalize content item density. In one technique, an entity that is associated with a content request is identified. Multiple sets of content items are identified that includes content items of different types. A first position of a first slot is determined in a content item feed that comprises multiple slots. A second position of a previous content item is determined, in the content item feed, that is of a first type. A difference between the first position and the second position is determined. Based on the difference, a gap sensitivity value that is associated with the entity and is different than the difference is determined. Based on the gap sensitivity value, a content item from the multiple sets of content items is selected and inserted into the first slot. The content item feed is transmitted to a computing device to be presented thereon.
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公开(公告)号：US10951676B2
公开(公告)日：2021-03-16
申请号：US16141642
申请日：2018-09-25
摘要： Techniques for varying content item density are provided. A first minimum gap value is stored that dictates how close two content items of a first type may appear in a content item feed that contains content items of multiple types that includes the first type and a second type. The first minimum gap value is used to place content items in a first set of content item feeds. For each content item feed of the first set of content item feeds, performance data that indicates how well content items of the first type perform in the content item feed is generated. Based on the performance data and the first minimum gap value, a second minimum gap value that is different than the first minimum gap value is generated. The second minimum gap value is used to place content items in a second plurality of content item feeds.
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公开(公告)号：US10853736B2
公开(公告)日：2020-12-01
申请号：US15816304
申请日：2017-11-17
发明人： Jinyun Yan , Peng Du , Shaunak Chatterjee , Shipeng Yu
IPC分类号： G06N7/00 , G06Q50/00 , G06Q10/10 , G06N20/00 , G06F3/0481
摘要： A method can include determining, based on learned parameter values, an intrinsic interest and an affinity for the user to be influenced to visit the website, determining, using the learned parameter values, intrinsic interest, and affinity for the user to be influenced to visit the website, a first probability indicating a likelihood that the user will, in response to viewing a badge notification, turn off notifications or delete an app and a second probability indicating a likelihood that the user will, in response to viewing the badge notification on the app, visit a website, in response to determining the second probability is greater than a threshold larger than the first probability, causing the app to include the badge notification when displayed on the user device.
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