ONLINE SOCIAL NETWORK MEMBER PROFILE TAXONOMY

1 . A method comprising:

retrieving, by a server computer system from a database, a first profile of a first member of an online social network;

comparing, by the server computer system, content items within the retrieved first profile to content items stored in a database to identify a new content item that is present in the first profile and not present in the database, wherein identifying the new content item includes performing one or more of: a similarity mapping that generates a respective similarity score for the new content item and each respective content item in the database, and a shared-word lapping that identifies one or more words in common between the new content item and the content items stored in the database;

storing, by the server computer system, the new content item in the database;

retrieving, by the server computer system from the database, a second profile of a second member of the online social network;

determining, by the server computer system, a level of similarity between a content item contained within the second profile and the new content item; and

transmitting, by the server computer system over the Internet, an electronic communication to a computing device of the second member identifying the new content item for possible inclusion in the second profile.

2 . The method of claim 1 , wherein the new content item comprises one or more of: a new skill, a new phrase associated with an existing skill, and a new phrase associated with a new skill.

3 . The method of claim 1 , wherein identifying the new content item includes identifying a type for the new content item and modifying a data structure associated with the new content item to include the identified type.

4 . The method of claim 3 , wherein identifying the new content item further includes modifying the data structure associated with the new content item to include one or more of: an identifier, a definition, and a synonym for the identified type.

5 . The method of claim 4 , wherein identifying the new content item further includes modifying the data structure associated with the new content item to include an identifier that is a phrase selected from the first profile.

6 . The method of claim 5 , wherein selecting the phrase from the first profile includes:

identifying a plurality of phrases within the first profile;

converting each respective phrase in the plurality of phrases into a respective vector to generate a plurality of vectors;

identifying ambiguous phrases and unambiguous phrases in the plurality of phrases by applying a clustering algorithm to the plurality of vectors; and

selecting the phrase from the first profile from among the unambiguous phrases.

7 . The method of claim 6 , wherein applying the clustering algorithm to the plurality of vectors includes identifying synonyms and duplicate phrases.

8 . The method of claim 5 , wherein selecting the phrase from the first profile includes translating the selected phrase from a first language to a second language, and including the phrase in the second language in the data structure.

9 . The method of claim 1 , wherein generating the similarity score for the new content item includes generating a similarity score that is a maximum of a world-level Jaccard similarity score and a character-level Levenstein similarity score.

10 . The method of claim 9 , wherein identifying the new content item includes selecting the new content item based on the generated similarity score meeting or exceeding a predetermined threshold.

11 . The method of claim 1 , wherein the new content item includes an attribute associated with one or more of: a member of the online social network, a job, a title, a skill, an organization, a geographical location, and an educational institution.

12 . The method of claim 11 , wherein the new content item includes a first attribute having a relationship to one or more content items stored in the database, and a second attribute that is unrelated to the content items stored in the database.

13 . The method of claim 12 , wherein the relationship to the one or more content items for the first attribute is defined by the first member.

14 . The method of claim 12 , wherein the relationship to the one or more content items for the first attribute is determined by the server computer system based on the content items within the first profile.

15 . The method of claim 14 , wherein determining the relationship to the one or more content items for the first attribute includes:

identifying a plurality of member-defined attribute relationships in a plurality of member profiles stored in the database;

applying a binary classifier process that determines the relationship to the one or more content items for the first attribute based on the plurality of member-defined attribute relationships.

16 . The method of claim 11 , wherein identifying the new content item includes generating a confidence score for the attribute reflecting a level of accuracy of the attribute.

17 . The method of claim 1 , further comprising generating, by the server computer system, a graph that visually represents the new content item in relation to the content items stored in the database.

18 . The method of claim 17 , wherein the graph depicts content items having a relatively higher similarity to each other in relatively closer proximity to each other, and content items having a relatively lower similarity to each other in relatively farther proximity to each other.

19 . A system comprising:

a processor; and

memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising:

retrieving, from a database, a first profile of a first member of an online social network;

comparing content items within the retrieved first profile to content items stored in a database to identify a new content item that is present in the first profile and not present in the database, wherein identifying the new content item includes performing one or more of a similarity mapping that generates a respective similarity score for the new content item and each respective content item in the database, and a shared-word mapping that identifies one or more words in common between the new content item and the content items stored in the database;

storing the new content item in the database;

retrieving, from the database, a second profile of a second member of the online social network;

determining a level of similarity between a content item contained within the second profile and the new content item; and

transmitting, over the Internet, an electronic communication to a computing device of the second member identifying the new content item for possible inclusion in the second profile.

20 . A tangible, non-transitory computer-readable medium storing instructions that, when executed by a server computer system, cause the server computer system to perform operations comprising:

retrieving, from a database, a first profile of a first member of an online social network;

comparing content items within the retrieved first profile to content items stored in a database to identify a new content item that is present in the first profile and not present in the database, wherein identifying the new content item includes performing one or more of a similarity mapping that generates a respective similarity score for the new content item and each respective content item in the database, and a shared-word mapping that identifies one or more words in common between the new content item and the content items stored in the database;

storing the new content item in the database;

retrieving, from the database, a second profile of a second member of the online social network;

determining a level of similarity between a content item contained within the second profile and the new content item; and

transmitting, over the Internet, an electronic communication to a computing device of the second member identifying the new content item for possible inclusion in the second profile.