GENERATING RECOMMENDED RESPONSES BASED ON HISTORICAL MESSAGE DATA

    公开(公告)号:US20190124019A1

    公开(公告)日:2019-04-25

    申请号:US15884772

    申请日:2018-01-31

    IPC分类号: H04L12/58 G06F3/0484

    摘要: Disclosed are systems, methods, and non-transitory computer-readable media for generating recommended responses based on historical data. A messaging system receives a message as part of a communication session between a first client device and a second client device. The message originated from the first client device. The messaging system determines, using the message as input in a statistical model, a set of candidate responses for replying to the message. The statistical model was generated based on historical message data transmitted as part of previous communication sessions between a plurality of client devices. The set of candidate responses is a subset of a set of available candidate responses. The messaging system determines, based on a set of candidate selection rules, a subset of the candidate responses yielding a set of recommended responses to the message, and causes the set of recommended responses to be presented on the second client device.

    SHARING CONTENT TO MULTIPLE PUBLIC AND PRIVATE TARGETS IN A SOCIAL NETWORK

    公开(公告)号:US20190190875A1

    公开(公告)日:2019-06-20

    申请号:US15847304

    申请日:2017-12-19

    IPC分类号: H04L12/58 G06N99/00 G06F17/30

    摘要: Described herein is a technique to facilitate the sharing of a content item presented in a content feed of a social networking service. Upon detecting that a member has selected an option to share a content item, a content sharing interface is presented. The content sharing interface includes options share the content item publically via a content feed, and privately via a messaging service. The content sharing interface provides a ranked list of recommended recipients, where the recommended recipients in the list are selected and ordered based on several factors, including factors relating to the relationship between the sharing member and the recommended recipients, as well as factors relating to the subject matter of the content item and the likelihood that a recommended recipient would be interested in the content item.