发明名称 |
Ranking Recommended Search Queries on Online Social Networks |
摘要 |
In one embodiment, a method includes accessing a social graph that includes a number of nodes and edges connecting the nodes. Each of the edges between two of the nodes representing a single degree of separation between them. The nodes include a first node corresponding to a first user associated with an online social network and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network. The method also includes generating a card cluster including a number of cards. Each card includes a suggested query referencing a query-domain associated with the online social network and zero or more query-filters. Each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges. |
申请公布号 |
US2015178284(A1) |
申请公布日期 |
2015.06.25 |
申请号 |
US201414259001 |
申请日期 |
2014.04.22 |
申请人 |
Facebook, Inc. |
发明人 |
Garg Avichal;Hua Ming;Vernal Michael;Qin Yang;Fechete Dan Ionut |
分类号 |
G06F17/30;H04L29/08 |
主分类号 |
G06F17/30 |
代理机构 |
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代理人 |
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主权项 |
1. A method comprising, by a computing device:
accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising:
a first node corresponding to a first user associated with an online social network; anda plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a card cluster comprising a plurality of cards, each card comprising a suggested query referencing a query-domain associated with the online social network and zero or more query-filters, wherein each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges; calculating a predicted click-thru rate (CTR) for each card in the card cluster based on one or more user-engagement factors; ranking each of the cards in the card cluster based on the predicted CTR; and sending the card cluster to the first user for display on a page currently accessed by the first user, the cards of the card cluster being ordered based on the rankings associated with the cards. |
地址 |
Menlo Park CA US |