Abstract: Methods, systems, apparatus, and articles of manufacture to augment training data based on synthetic images are disclosed. An example apparatus disclosed herein includes programmable circuitry to generate, with one or more first layers of a generative adversarial network (GAN), a latent representation corresponding to a first image representative of a first racial domain, generate, with one or more second layers of the GAN, a second image based on the latent representation, the second image corresponding to a second racial domain different from the first racial domain, and augment a training dataset based on the second image.

Abstract: Systems and methods for displaying a user interface object associated with a job candidate's social networking site proximate to a job listing presented by a website are described. When a job candidate selects the user interface object, the systems and methods identify and/or obtain information associated with the job candidate that is located or otherwise stored at the social networking site of which the job candidate is a member. Once the information is identified and/or obtained, the systems and methods provide the information to the website, such as to a job application submission system associated with the website.

Abstract: Techniques for identifying and presenting member profiles similar to a source member profile are described. With some embodiments, a general recommendation engine is used to extract features from member profiles, and then store the extracted features, including any computed, derived or retrieved profile features, in an enhanced member profile. In real-time, the general recommendation engine processes client requests to identify member profiles similar to a source member profile by comparing select profile features stored in the enhanced member profile with corresponding profile features of the source member profile, where the comparison results in several similarity sub-scores that are then combined in accordance with directives set forth in a configuration file. Finally, the member profiles with the highest similarity scores corresponding with the user-selected member profile are selected, and in some instances, presented to a user.

Abstract: The disclosed embodiments provide a method and system for performing regularized model adaptation for in-session recommendations. During operation, the system obtains, from a server, a first global version of a statistical model. During a first user session with a user, the system improves a performance of the statistical model by using the first global version to output one or more recommendations to the user and using the first global version and user feedback from the user to create a first personalized version of the statistical model. At an end of the first user session, the system transmits an update containing a difference between the first personalized version and the first global version to the server for use in producing a second global version of the statistical model by the server.

Abstract: Techniques for leveraging a social graph to facilitate the delivery of relevant recommendations. For example, a recommender is identified based on the recommender being a member of a social networking service who has interacted with an item of web-based content. A recommendee is identified based on the recommendee being another member of the social networking service who is connected to the recommender via a social graph maintained by the social networking service and based on having an affinity score for the item that exceeds a recommendee affinity score threshold and a connection strength to the recommender that exceeds a connection strength threshold. The recommender is sent a communication that invites the recommender to recommend the item to the recommendee. With some example embodiments, the communication is sent to the recommender within a pre-determined time measured from the time the recommender initiated an interaction with the item of web-based content.

Abstract: A system and method for managing asynchronously receiving updates and merging updates into global versions of a statistical model using version control are disclosed. During operation, the system transmits a first global version of a statistical model to a set of client computer systems. Next, the system obtains, from a first subset of the client computer systems, a first set of updates to the first global version. The system then merges the first set of updates into a second global version of the statistical model. Finally, the system transmits the second global version to the client computer systems asynchronously from receiving a second set of updates to the first and/or second global versions from a second subset of the client computer systems.

Abstract: Disclosed in some examples are methods, systems and machine readable medium for recommending an out-of-network communication by determining a set of potential recommended members of a social networking service based upon one or more recommendation criteria. In some examples the recommendation criteria may include: a profile similarity to a previous target of an out-of-network communication, a degree of correspondence between an interest and intent of the sending member, and a likelihood of response.

Abstract: A method and system for providing account recommendations is disclosed. A server system stores sales data for a first member, wherein sales data includes profile information for one or more individual customers. The server system analyzes the profile information for one or more of the individual customers to identify one attributes associated with the customers. The server system determines one or more additional members with member profiles that include the one or more identified attributes. For a respective additional member in the at least one of the determined additional members the server system determines, based on stored information about the respective additional member, an respective organization associated with the at least one determined additional member; and selects the respective organization as an account recommendation.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: Techniques for generating recommendation cluster within a social network service are described. Consistent with some embodiments, sample members in a social network service are identified. The sample members may be associated with prior member activity involving a source member. A cluster category this then selected based on a member attribute shared by a plurality of the sample members. In turn, a recommendation cluster is generated based on the selected cluster category. Generating the recommendation duster may involve selecting member profiles that match the cluster category. The member profiles selected in this way form the recommendation cluster. One or more of the member profiles of the recommendation cluster are then surfaced to a client device operated by the source member.

Abstract: A first user of a presentation machine may be a recruiter that initiates an action in reference to a first user profile. The first user profile may describe a first candidate for a job. The presentation machine may identify the first user profile and determine a similarity score that indicates a degree of similarity between the first user profile and a second user profile that describes a second candidate for the job. The presentation machine may also access a volatility score that indicates a likelihood that the second candidate is receptive to a proposal that the second candidate be employed by an employer. Based on the similarity score and on the volatility score, the presentation machine may determine a rank of the second user profile. Based on the determined rank, the presentation machine may present the second user profile to the first user.

Abstract: A method and system for providing account recommendations is disclosed. A server system stores sales data for a first member, wherein sales data includes profile information for one or more individual customers. The server system analyzes the profile information for one or more of the individual customers to identify one attributes associated with the customers. The server system determines one or more additional members with member profiles that include the one or more identified attributes. For a respective additional member in the at least one of the determined additional members the server system determines, based on stored information about the respective additional member, an respective organization associated with the at least one determined additional member; and selects the respective organization as an account recommendation.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: A method and system for providing account recommendations is disclosed. A server system stores sales data for a first member, wherein sales data includes profile information for one or more individual customers. The sewer system analyzes the profile information for one or more of the individual customers to identify one attributes associated with the customers. The server system determines one or more additional members with member profiles that include the one or more identified attributes. For a respective additional member in the at least one of the determined additional members the server system determines, based on stored information about the respective additional member, an respective organization associated with the at least one determined additional member; and selects the respective organization as an account recommendation.

Abstract: A method and system for providing lead recommendations are disclosed. A server system stores profile information for a plurality of members of a server system. The server system then analyzes the stored profile information to identify one or more potential sales lead recommendations for a first member of the server system. The server system then ranks the one or more identified potential sales lead recommendations. The server system selects one or more of the identified sales lead recommendations and transmits the selected one or more identified sales lead recommendations to a client device associated with the first member of the server system.

Abstract: This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.

Abstract: A system and method for temporal-based professional similarity are provided. In example embodiments, a request to identify, from among a plurality of member profiles of a social network service, a profile that is similar to a source profile, is received. Profile data of the source profile and a candidate profile are accessed from the social network service. Profile features are extracted from the profile data. The profile features include source features extracted from the profile data of the source profile and candidate features extracted from the profile data of the candidate profile. Respective profile features correspond to temporal data included in the profile data. Data structures are generated by structuring the profile features according to the temporal data. The data structures include a source data structure generated using the source features and a candidate data structure generated using the candidate features.

Abstract: Systems and methods are disclosed for determining whether a short amount of text is irrelevant. Initially, an article is selected having one or more comments of varying length. Depending on the number of comments available, a native context may be constructed based on a given comment and other neighboring comments. In other embodiments, a transferred context may be constructed from the given comment and topically similar comments extracted from other, topically similar articles. A native context-aware feature may be determined from the constructed native context and a transferred context-aware feature may be determined from the constructed transferred context. These features may be leveraged by a language classifier to determine whether a given comment is irrelevant.

Abstract: A system may include a network interface and a batch processor coupled to the network interface. The batch processor may be configured to obtain social network profiles corresponding to entities and to obtain a target criterion. The batch processor may be configured to identify at least some of the entities based on a relationship between the social network profiles and the target criterion and to transmit, via the network interface, a data file to a computing device of the at least some of the entities, wherein the data file contains information related, at least in part, to the target criterion.

Abstract: A statistically overrepresented token in the descriptions of users associated with a target entity may be descriptive of the target entity. This may be true regardless of whether a primary description of the entity includes the overrepresented token. Accordingly, the entity description machine may access multiple descriptions of multiple users associated with the target entity. A portion of the multiple descriptions may each include a token descriptive of the target entity and of a subset of the multiple users. The entity description machine may determine that the token is overrepresented among the tokens within the multiple descriptions and generate a supplemental description of the target entity, where the supplemental description includes the overrepresented token. Once the supplemental description is generated, the entity description machine may use the supplemental description in referencing the target entity.