Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: In an example, disclosed is a machine automated method of identifying a set of skills. In some examples, the method includes extracting a plurality of skill seed phrases from a plurality of member profiles of a social networking site, creating a plurality of disambiguated skill seed phrases by disambiguating the plurality of skill seed phrases using one or more computer processors, and de-duplicating the plurality of disambiguated skill seed phrases to create a plurality of de-duplicated skill seed phrases.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Disclosed in some examples are methods, machine readable mediums, and systems which build upon traditional frameworks such as Hadoop for developing incremental monoid computations. In some examples, the traditional frameworks requires no modifications, and may provide an accumulator-based interface for programmers to store and use state across successive runs; the framework may ensure that only the necessary sub-computations are performed and incremental state management may be hidden from the programmer.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: In an example, disclosed is a machine automated method of identifying a set of skills. In some examples, the method includes extracting a plurality of skill seed phrases from a plurality of member profiles of a social networking site, creating a plurality of disambiguated skill seed phrases by disambiguating the plurality of skill seed phrases using one or more computer processors, and de-duplicating the plurality of disambiguated skill seed phrases to create a plurality of de-duplicated skill seed phrases.

Abstract: In an example, disclosed is a machine automated method of identifying a set of skills. In some examples, the method includes extracting a plurality of skill seed phrases from a plurality of member profiles of a social networking site, creating a plurality of disambiguated skill seed phrases by disambiguating the plurality of skill seed phrases using one or more computer processors, and de-duplicating the plurality of disambiguated skill seed phrases to create a plurality of de-duplicated skill seed phrases.

Abstract: Disclosed in some examples is a method of inferring one or more attribute values of a member of a social networking service by collecting a plurality of attribute values associated with attributes of a plurality of members of a social networking service, the plurality of attribute values including member profile information; and inferring one or more attribute values regarding a particular member in the plurality of members based upon the collected plurality of attribute values and a plurality of collected attribute values of the particular member.

Abstract: In an example, disclosed is a machine automated method of identifying a set of skills. In some examples, the method includes extracting a plurality of skill seed phrases from a plurality of member profiles of a social networking site, creating a plurality of disambiguated skill seed phrases by disambiguating the plurality of skill seed phrases using one or more computer processors, and de-duplicating the plurality of disambiguated skill seed phrases to create a plurality of de-duplicated skill seed phrases.

Abstract: Disclosed herein are methods and systems for customizing content for presentation via a social or business networking service. In some examples, a method may involve an automated mechanism for identifying a plurality of members (e.g., member profiles) to indicate a particular skill possessed by the respective members. Next, the method may involve ranking the plurality of tagged members relative to one another based on a calculated skill level of the particular skill using a computer processor and generating customization information based upon member profile information in the member profiles of the plurality of members with the particular skill and the rankings of the members who possess the particular skill and causing the customization information to be delivered to one of the plurality of members with a particular skill.

Abstract: In an example disclosed is a method of ranking social networking service member skills by retrieving from non-volatile storage a plurality of member profiles created by a plurality of members of a social networking service, running a text classification algorithm to determine which of the plurality of members possesses a skill that matches any of a plurality of provided skills and associated skill attributes; and for at least one skill of the plurality of provided skills, identifying the plurality of members that possess the skill and ranking the plurality of members relative to one another using a ranking algorithm, the ranking algorithm being based in part upon weighted interactions among the plurality of members that possess the given skill, the weighted interactions comprising endorsements between a first member who possesses the given skill and a second member who possesses the given skill.