Facebook, Inc.

Jasper Reid Hauser

Luke St Clair

Jenny Yuen

David Harry Garcia

Shaheen Ashok Gandhi

William Samuel Bailey

Henry Bridge

Jonathan M Kaldor

Vladimir Kolesnikov

Majd Jack Taby

Jasleen Singh

Dan Ionut Fechete

Vijay Kumar Sivakumar

Michael Andrew Howard

Xun Gong

Xuan Jiang

Zhiyuan Zhang

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

Particular embodiments may locally store, at a client device of a first user, information associated with a plurality of nodes and a plurality of edges of a social graph received from a social-networking system. The first user may be associated with a first node of the social graph. The client device may detect that the first user is entering an input term. The client device may provide predictive typeahead results as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may correspond to one of the nodes of the social graph stored locally on the client device. Each predictive typeahead result may include at least one image associated with the corresponding node.

Enhanced predictive input utilizing a typeahead process

In one embodiment, a computing device determines a size of a view port of a graphical user interface based on a scrolling frame rate, processing resources, or memory resources of the computing device. One or more content objects are displayed in the view port. A scroll region for the user to scroll within is determined and the scroll region is independent of the boundaries of the displayed content objects. A first touch gesture across one or more boundaries of the displayed content objects is received. A velocity of the first touch gesture motion is determined. When the velocity is less than or equal to a threshold velocity, the computing device scrolls to an adjacent content object of the current displayed content object. When the velocity is higher than the threshold velocity, the computing device scrolls to advance multiple content objects with respect to the current displayed content object.

Infinite bi-directional scrolling

In one embodiment, logic embodied in a computer-readable non-transitory storage medium of a device determines a location of a touch gesture by a user within a touch-sensitive area of the device. The logic selects for the touch gesture based on its location within the touch-sensitive area one of a plurality of pre-determined offsets, the pre-determined offsets being specific to the device, the pre-determined offsets being derived from device-specific empirical data on usage of the device by a plurality of users, and the pre-determined offsets being pre-loaded onto the device. The logic applies the pre-determined offset to the location of the touch gesture to determine a touch input intended by the user.

Touch gesture offset

In one embodiment, a method includes providing for display to a user content including multiple content objects that each has a boundary defining a two-dimensional area. A two-dimensional scroll region for user scrolling within the content is determined. The two-dimensional scroll region is independent of the two-dimensional areas of the content objects. User input to scroll within the content in one or both of the two dimensions across one or more of the boundaries is received. The method includes scrolling within the content according to the user input, the scrolling being continuous across the boundaries.

Using clamping to modify scrolling

Scrolling across boundaries in a structured document

Particular embodiments may store, at a client device, information associated with nodes and edges of a social graph. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of the social graph. A first user may be associated with a first user node of the social graph. The client device may receive a character string from the first user, and identify, as the first user inputs the character string, an edge-type based on the character string and one or more edges of the identified edge-type, wherein the edges are locally stored on the client device. The client device may display one or more predictive typeahead results based on the identified edge-type and the identified edges. The predictive typeahead results may correspond to nodes stored locally on the client device.

In one embodiment, a method includes detecting one or more user interactions, associated with a user of a computing device, each interaction occurring at a region associated with an input value, and determining, for at least one user interaction, that the at least one user intended to provide a different input value. Adaptation information is generated for the at least one user based on the at least one user interaction. The adaptation information is stored for the at least one user. A user interaction is detected at a region. The user's intended input value is determined based on the user interaction and the adaptation information.

Systems and methods for a user-adaptive keyboard

Particular embodiments may retrieve information associated with one or more nodes of a social graph from one or more data stores. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of a social graph. A first user may be associated with a first user node of the social graph. Particular embodiments may detect that the first user is entering an input term. Predictive typeahead results may be provided as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may include at least one image. Each predictive typeahead result may correspond to at least one node of the social graph.

Particular embodiments determine that a textual term is not associated with a known meaning. The textual term may be related to one or more users of the social-networking system. A determination is made as to whether the textual term should be added to a glossary. If so, then the textual term is added to the glossary. Information related to one or more textual terms in the glossary is provided to enhance auto-correction, provide predictive text input suggestions, or augment social graph data. Particular embodiments discover new textual terms by mining information, wherein the information was received from one or more users of the social-networking system, was generated for one or more users of the social-networking system, is marked as being associated with one or more users of the social-networking system, or includes an identifier for each of one or more users of the social-networking system.

Growing community of inventors

San Francisco, CA, United States of America

Jasper Reid Hauser