Facebook, Inc.

Dan Ionut Fechete

Yang Qin

Ming Hua

Michael Steven Vernal

Avichal Garg

Yu Huang

Alex Himel

Lu D Chen

Saurabh Prafulla Chakradeo

Xinpan Xiao

Dharmesh A Bhatt

Jasper Reid Hauser

Vijay Kumar Sivakumar

Xun Gong

Zhong Zhang

Michael Andrew Howard

Zhiyuan Zhang

Xuan Jiang

Sergiu-Cosmin Ferentz

Scott Joseph Robert Horsfall

In one embodiment, a method includes identifying one or more social network events that satisfy a query condition in a social-networking system, determining an event score for each of the identified events, where the event score is based on one or more signals that are each related to a first interaction between a target user and the social-networking system, and the first interaction associates the target user with the identified event, and presenting one or more of the identified events to the target user in an order based on the event score of each identified event. The interaction may establish an association between the target user and an entity associated with the event.

Events discovery context

In one embodiment, a method includes, in an online social network, accessing one or more first content objects associated with a user in the online social network and a second content object, determining topics and corresponding first weights of the topics for the first content objects using a topic extraction algorithm, where each first weight indicates a strength of an association between the corresponding topic and the first content object(s), determining one or more second weights of the topics for the second content object, where each second weight indicates a strength of an association between the corresponding topic and the second content object, and calculating a similarity score for the second content object based on a comparison of, for each topic, the first weight to the second weight, where the similarity score is to be used in a determination regarding presentation of the second content object to the user.

Identifying content for users on online social networks

In one embodiment, a method includes receiving, from a client system of a first user of the communication system, an input from the first user to access a card-stack interface, generating a card cluster comprising a plurality of cards, each card comprising a suggested query referencing a query-domain and one or more query-filters, wherein each query-filter references one or more objects associated with the communication system, and wherein each card in the card cluster is ranked within the card cluster based on a predicted click-thru rate (CTR) for the card based on one or more user-engagement factors, and sending, to the client system in response to the input from the first user, the card-stack interface for display to the first user, wherein the card-stack interface comprises the card cluster, the cards of the card cluster being ordered based on the rankings associated with the cards.

Ranking recommended search queries

In one embodiment, a method includes receiving, from a client device of a user of an online social network, an input from the user to access a card-stack interface, generating a plurality of cards, where each card comprises a suggested query referencing a query-domain associated with the online social network and one or more query-filters, and where each query-filter references one or more objects of the online social network, each card further comprising one or more search results corresponding to the suggested query, and each search result referencing an object of the online social network matching the suggested query of the card; and sending, to the client device in response to the input from the first user, the card-stack interface for display to the first user, wherein the card-stack interface comprises one or more of the generated cards.

Generating card stacks with queries on online social networks

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.

Ranking recommended search queries on online social networks

Exemplary methods, apparatuses, and systems receive a candidate object with which a user can interact within a network service. For each of a first plurality of objects with which the user has had a positive interaction, a first value representing a commonality between the candidate object and each of the first plurality of objects is determined. For each of a second plurality of objects with which a user has had a negative interaction, a second value representing a commonality between the candidate object and each of the second plurality of objects is determined. An aggregate positive distance is determined using a plurality of the first values. An aggregate negative distance is determined using a plurality of the second values. The candidate object is displayed or not displayed to the user as a recommendation based upon a difference between the aggregate positive distance and the aggregate negative distance.

Object recommendation based upon similarity distances

In one embodiment, a method includes accessing a social graph including a number of nodes and a number of edges connecting the nodes. Each of the edges between two of the nodes represent 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 number 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 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 for the query-domain. Each query-filter references one or more nodes of the number of nodes or one or more edges of the number of edges.

Generating recommended search queries on online social networks

Growing community of inventors

Mountain View, CA, United States of America

Dan Ionut Fechete