Facebook, Inc.

Chun-Yang Chen

Ching-Chih Weng

Kuan-Yu Tseng

Alessandro Presta

Yueh-Hsuan Chiang

Po-Lung Chen

Zhongxian Chen

Dmytro Molkov

Madhu Ramanathan

Lin-Shun Huang

Lin-Shung Huang

Ramkumar Venkat Vadali

Taroon Mandhana

Joydeep Sen Sarma

In one embodiment, a method includes receiving a search query, searching a multiple verticals to identify multiple of sets of objects in each respective vertical that match the search query, wherein each vertical stores objects of a particular object-type, generating a set of blended search results by blending the sets of identified objects from each vertical, determining that greater than a threshold proportion of objects in the set of blended search results are from a first vertical, adding at least one object from a second vertical to the set of blended search results in responsive to determining that greater than the threshold proportion of objects in the blended search results are from the first vertical, wherein the second vertical is different from the first vertical; and sending, responsive to the search query, the set of blended search results for display.

Blending search results on online social networks

In one embodiment, an online social network may receive, from a client system of a first user of the online social network, a search query inputted by the first user; and identify one or more of the entities matching the search query. At least a portion of the entities being identified based at least in part on a recorded geographic proximity between the first user and each identified entity. The online social network may access one or more proximity coefficients for the identified entities from a proximity-coefficient system of the online social network; calculate a score for each identified entity based at least in part on the value of the accessed proximity coefficients for the identified entity and social-graph information associated with the identified entity; and send, to the client system of the first user in response to the received search query, search results for display to the first user.

Proximity-based searching on online social networks

Techniques for asynchronous rendering are described. An apparatus may comprise a character set converter application, an index server, and a ranking application. The character set converter application may receive a search string comprised of one or more first character set characters, and convert the search string to one or more second character set characters that are different than the first character set. The index server may execute a search on the converted search string to obtain ranked individual search results. The ranking application may compare any first character set characters in the ranked individual search results to the first character set characters in the search string and sub-rank the ranked individual search results based on the strength of any matches. Other embodiments are described and claimed.

Techniques for ranking character searches

In one embodiment, a method includes receiving a search query from a user of an online social network and searching multiple verticals to identify multiple sets of objects in each vertical, respectively, that match the search query, and wherein each vertical stores one or more objects associated with the online social network. The method also includes ranking, for each set of identified objects from a vertical, each identified object in the set of identified objects. The method further includes blending the multiple sets of identified objects from each vertical to form a set of blended search results that includes a threshold number of identified objects, the blending including an iterative process performed at least the threshold number of iterations. Each iteration of the iterative blending process includes determining a blender score for each top-ranked identified object in each set of identified objects.

A system and method of managing a cluster of distributed machines is described. A cluster manager receives status updates regarding tasks running on each machine in the cluster from a task tracker running on the machine. The cluster manager receives resource requests from a job tracker created by a client wishing to run a job in the cluster. The cluster manager is responsible for implementing push-based fair scheduling of resources to the job trackers. The job tracker is responsible for running tasks for one job in the resource identified by the cluster manager. In one embodiment, the job tracker can run in the client for small jobs and in the cluster for larger jobs. The cluster manager can also be restarted, for example, for software updates without restraining the cluster.

Growing community of inventors

Sunnyvale, CA, United States of America

Chun-Yang Chen