Abstract: Methods, systems and computer program products for identifying a relationship between sub-units of an entity are described. The sub-units are segmented into one or more candidate related groups based on one or more general attributes and a pair of the sub-units of the one or more candidate related sub-units is selected. The pair of sub-units is analyzed to determine a relationship between the sub-units and the relationship between the sub-units is identified based on the determined relationship.

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: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The determination module accesses member profiles from a social network. Additionally, the determination module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the determination module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the determination module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles.

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: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The module accesses member profiles from a social network. Additionally, the module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles. Subsequently, the module may determine that the suggested location is a physical location when the calculated connection density is above a pre-determined threshold value.

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: Systems and methods are disclosed that recommend one or more electronic presentations to a user based on one or more factors. These factors may include contextual information, behavioral information, profile information, or combinations of the foregoing. Contextual information may include content and/or features extracted from a given electronic presentation. Behavioral information may include user behavioral data, such as the number of times a user has viewed a presentation, the amount of the presentation viewed by the user, presentations previously viewed by the user, and other such behavioral data. Profile information may include user professional profile information, such as skills the user has identified as possessing, employment history information, and other such user professional profile information.

Abstract: A method of receiving input from a user includes providing a surface within reach of a hand of the user. A plurality of locations on the surface that are touched by the user are sensed. An alphanumeric character having a shape most similar to the plurality of touched locations on the surface is determined. The user is audibly or visually informed of the alphanumeric character and/or a word in which the alphanumeric character is included. Feedback is received from the user regarding whether the alphanumeric character and/or word is an alphanumeric character and/or word that the user intended to be determined in the determining step.

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: The disclosed systems and methods are directed to detecting spam in an electronic presentation and determining whether the electronic presentation should be moderated. The example systems and methods may employ one or more classifiers for classifying an electronic presentation and, should the electronic presentation fall within a predetermined classification, the electronic presentation may be analyzed further for the presence of spam. Further analysis of the electronic presentation may include invoking one or more filters to determine whether the electronic presentation includes words and/or phrases known to be associated with spam. Where the electronic presentation is determined to contain spam, the electronic presentation may be removed from a database of electronic presentations, excluded from search results, or flagged for moderation by a moderator.

Abstract: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The determination module accesses member profiles from a social network. Additionally, the determination module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the determination module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the determination module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles.

Abstract: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The module accesses member profiles from a social network. Additionally, the module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles. Subsequently, the module may determine that the suggested location is a physical location when the calculated connection density is above a pre-determined threshold value.

Abstract: Systems and methods are disclosed that recommend one or more electronic presentations to a user based on one or more factors. These factors may include contextual information, behavioral information, profile information, or combinations of the foregoing. Contextual information may include content and/or features extracted from a given electronic presentation. Behavioral information may include user behavioral data, such as the number of times a user has viewed a presentation, the amount of the presentation viewed by the user, presentations previously viewed by the user, and other such behavioral data. Profile information may include user professional profile information, such as skills the user has identified as possessing, employment history information, and other such user professional profile information.

Abstract: Methods, systems and computer program products for identifying a work function of a company at a location and for identifying a work function of a group of workers are described. Members having member profiles that indicate employment at a company and at a location are segmented into one or more groups based on one or more job skills. One or more of the groups are analyzed to determine a work function of the location. The location of the company is identified based on the determined work function.

Abstract: Methods, systems and computer program products for identifying a relationship between sub-units of an entity are described. The sub-units are segmented into one or more candidate related groups based on one or more general attributes and a pair of the sub-units of the one or more candidate related sub-units is selected. The pair of sub-units is analyzed to determine a relationship between the sub-units and the relationship between the sub-units is identified based on the determined relationship.

Abstract: Methods, systems and computer program products for identifying a relationship between a plurality of entities are described. Members of an entity are segmented into one or more groups based on one or more attributes; one or more of the groups are analyzed to determine a function of the corresponding group. A pair of groups is selected, each group of the pair of groups being from a different entity. A relationship between the selected pair of groups is analyzed to generate a relationship metric, and the relationship between the selected pair of groups is characterized based on the relationship metric.

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: In an example embodiment, a similarity matching process is performed on one or more fields in account records obtained from a Customer Relationship Management (CRM) system and corresponding one or more fields in information obtained from a social network service to locate matches between one or more accounts in the account records for a first user and one or more company/organizations in the information obtained from the social network. Then a mapping is stored in a data store for each of the matches. The mappings are used to provide insights to the first user.

Abstract: Techniques to facilitate recommendations for sponsored content campaigns are described. Consistent with some embodiments, subsequent to a member of a social networking service specifying a desired objective to be achieved with a content campaign (e.g., increasing follower acquisition rate, or increasing a click-to-convert rate), a campaign optimization module provides, for a member-specified content posting, a recommended target audience that is most likely to react to the content posting in a manner that will enable the member to achieve the desired objective. Alternatively, a member may specify a desired objective and a target audience, and the campaign optimization module provides a recommendation as to the particular content posting that the member should promote or sponsor in order to achieve the desired objective.

Abstract: Techniques to facilitate recommendations for sponsored content campaigns are described. Consistent with some embodiments, subsequent to a member of a social networking service specifying a desired objective to be achieved with a content campaign (e.g., increasing follower acquisition rate, or increasing a click-to-convert rate), a campaign optimization module provides, for a member-specified content posting, a recommended target audience that is most likely to react to the content posting in a manner that will enable the member to achieve the desired objective. Alternatively, a member may specify a desired objective and a target audience, and the campaign optimization module provides a recommendation as to the particular content posting that the member should promote or sponsor in order to achieve the desired objective.