Facebook, Inc.

Other

Mark Andrew Rich

Rousseau Newaz Kazi

Amaç Herdagdelen

Brett Matthew Westervelt

Christina Joan Sauper

Maykel Andreas Louisa Jozef Anna Loomans

Shuyi Zheng

Soorya Vamsi Mohan Tanikella

Adam Eugene Bussing

Yuval Kesten

Russell Lee-Goldman

Lada Ariana Adamic

Nidhi Gupta

Amy Campbell

David M Goldblatt

Andrew Rocco Tresolini Fiore

In one embodiment, a method includes accessing a first set of objects associated with an online social network, each object being associated with one or more comments. The method also includes generating a second set of objects from the first set of objects by applying a first filtering criteria to the first set of objects and scoring each object in the second set of objects based on the comments associated with each object. The method further includes generating a training set of objects from the second set of objects by selecting each object from the second set of objects having a score greater than a first threshold score, each object in the training set being associated with a first object-classification. The method further includes determining an object-classifier algorithm for the first object-classification, the object-classifier algorithm being determined through an iterative training process performed one or more times.

Iterative classifier training on online social networks

In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, n-grams from the text of the communication; identifying mention-terms from the extracted n-grams, each mention-term being a noun-phrase; calculating a term-score for each mention-term based on a frequency of occurrence of the mention-term in the communications; and generating a mentions-module including mentions, each mention including a mention-term having a term-score greater than a threshold term-score and text from communications comprising the mention-term.

Mentions-modules on online social networks

In one embodiment, a method includes receiving, from a client system of a first user, a request associated with a particular content item; identifying communications authored by one or more users, each identified communication being associated with the particular content item; generating one or more search-results modules related to the particular content item, each search-results module being of a particular module type, wherein each search-results module includes information from a subset of the identified communications, the information corresponding to the particular module type of the search-results module, and wherein a number of communications in the subset of the identified communications including each search-results module is greater than a module-specific threshold number of communications; and sending, to the client system, a search-results interface comprising one or more of the search-results modules.

Search-results interfaces for content-item-specific modules on online social networks

In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; calculating, for each of the communications, sentiment-scores corresponding to sentiments, wherein each sentiment-score is based on a degree to which n-grams of the text of the communication match sentiment-words associated with the sentiments; determining, for each of the communications, an overall sentiment for the communication based on the calculated sentiment-scores for the communication; calculating sentiment levels for the particular content item corresponding sentiments, each sentiment level being based on a total number of communications determined to have the overall sentiment of the sentiment level; and generating a sentiments-module including sentiment-representations corresponding to overall sentiments having sentiment levels greater than a threshold sentiment level.

Sentiment-modules on online social networks

In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, quotations from the text of the communication; determining, for each extracted quotation, partitions of the quotation; grouping the extracted quotations into clusters based on a respective degree of similarity among their respective partitions; calculating a cluster-score for each cluster based on a frequency of occurrence of partitions of quotations in the cluster in the communications; and generating a quotations-module comprising representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score.

Quotations-modules on online social networks

In one embodiment, a method includes receiving unstructured text from a user of a social-networking system, determining whether the unstructured text includes a request for a recommendation, identifying one or more first entity names in the unstructured text, generating a structured query based upon the one or more first entity names, identifying, in the social graph, one or more second entity names corresponding to the structured query, and presenting the one or more second entity names and the unstructured text in a social context of the user. The unstructured text may include text of a post or message generated by the user on a social-networking system. A score may be generated based on the unstructured text to determine whether the text includes a request for recommendation using a machine-learning model based on comparison of the unstructured text to the one or more predetermined words associated with requests for recommendation.

Identifying and processing recommendation requests

A surgical needle holder is provided in which the handle members are arranged in a plane at right angles to associated jaws which are operated by the handles. A camming arrangement is coupled between the handles and jaws to convert the movement of the handles in one plane to movement of the jaws in a second perpendicularly arranged plane. The needle holder is employed for suturing in surgical procedures and facilitates placement of the hand of the operator as well as the application of force in a rotary sense thereby.

Growing community of inventors

Redwood City, CA, United States of America

Mark Andrew Rich