Patent application number | Description | Published |
20140081928 | SKILL EXTRACTION SYSTEM - 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. | 03-20-2014 |
20140156675 | PRESENTING A USER PROFILE - 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. | 06-05-2014 |
20140195549 | SUGGESTED OUT OF NETWORK COMMUNICATION RECIPIENTS - 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. | 07-10-2014 |
20140351259 | GENERATING RECOMMENDATION CLUSTERS IN A SOCIAL NETWORK - 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. | 11-27-2014 |
20150081576 | GENERATING A SUPPLEMENTAL DESCRIPTION OF AN ENTITY - 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. | 03-19-2015 |
20150120714 | TEMPORAL-BASED PROFESSIONAL SIMILARITY - 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. A profile similarity score is determined by comparing the candidate data structure with the source data structure. The profile similarity score indicates the similarity between the candidate profile and the source profile. | 04-30-2015 |
20150134745 | METHODS AND SYSTEMS FOR IDENTIFYING MEMBER PROFILES SIMILAR TO A SOURCE MEMBER PROFILE - 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. | 05-14-2015 |
20150163190 | SUGGESTED OUT OF NETWORK COMMUNICATION RECIPIENTS - 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. | 06-11-2015 |