公开(公告)号：US20190042976A1

公开(公告)日：2019-02-07

申请号：US15666461

申请日：2017-08-01

Applicant: Facebook, Inc.

Inventor： Apaorn Tanglertsampan ,  Hannah Marie Hemmaplardh ,  Deepak Chinavle ,  Nigel Carter ,  Brendon Elias Manwaring ,  Bradley Ray Green

IPC: G06N99/00 ,  G06Q50/00 ,  G06N5/02

Abstract: Systems, methods, and non-transitory computer readable media can determine one or more actions that a user is likely to take on a page associated with a social networking system, based on one or more first machine learning models. One or more card types that correspond to the one or more actions can be ranked based on a second machine learning model. One or more cards can be generated based on the ranked card types, and each card can include a recommended action associated with the page.

公开(公告)号：US20180165302A1

公开(公告)日：2018-06-14

申请号：US15376287

申请日：2016-12-12

Applicant: Facebook, Inc.

Inventor： Apaorn Tanglertsampan ,  Jason Eric Brewer ,  Bradley Ray Green

IPC: G06F17/30 ,  H04L29/08

CPC classification number: G06F16/29 ,  G06F16/9537 ,  H04L67/18

Abstract: Systems, methods, and non-transitory computer readable media are configured to apply a spectral clustering technique to at least a portion of a similarity graph to generate clusters of geographic sub-regions constituting geographic regions. A tf-idf technique is performed to determine pages of a social networking system associated with a geographic region as potential local suggestions for a user associated with a geographic sub-region in the geographic region. References to at least a portion of the pages are presented as local suggestions to the user.

公开(公告)号：US20180107742A1

公开(公告)日：2018-04-19

申请号：US15297024

申请日：2016-10-18

Applicant: Facebook, Inc.

Inventor： Komal Kapoor ,  Apaorn Tanglertsampan ,  Bradley Ray Green ,  Meiying Li ,  James Donovan ,  Hannah Marie Hemmaplardh

IPC: G06F17/30 ,  G06N99/00 ,  G06Q50/00

CPC classification number: G06F16/9535 ,  G06F16/24578 ,  G06F16/248 ,  G06N20/00 ,  G06Q50/01

Abstract: Systems, methods, and non-transitory computer-readable media can train a machine learning model to determine predictive search recommendation based on search prediction information. Search prediction information associated with a user is provided to the machine learning model. A predictive search recommendation is presented to the user based on the machine learning model and the search prediction information. A search is performed based on the predictive search recommendation for one or more search results associated with entity pages on a social networking system.

公开(公告)号：US20180107741A1

公开(公告)日：2018-04-19

申请号：US15297007

申请日：2016-10-18

Applicant: Facebook, Inc.

Inventor： Komal Kapoor ,  Apaorn Tanglertsampan ,  Bradley Ray Green ,  Meiying Li ,  James Donovan ,  Hannah Marie Hemmaplardh

IPC: G06F17/30

CPC classification number: G06F16/9535 ,  G06F21/6218

Abstract: Systems, methods, and non-transitory computer-readable media can present a service directory landing page comprising a plurality of selectable service category options associated with a plurality of pre-defined service categories. A search results page is presented, including one or more search results based on search criteria. Each of the one or more search results is associated with an entity page of a social networking system. The service directory landing page and the search results page are accessible without logging into the social networking system. Each entity page on the social networking system is accessible only when logged into the social networking system.