Abstract: Embodiments of the described technologies are capable of reading a text sequence that include at least one word; extracting model input data from the text sequence, where the model input data includes, for each word of the text sequence, segment data and non-segment data; using a first machine learning model and at least one second machine learning model, generating, for each word of the text sequence, a multi-level feature set; outputting, by a third machine learning model, in response to input to the third machine learning model of the multi-level feature set, a tagged version of the text sequence; executing a search based at least in part on the tagged version of the text sequence.

Abstract: Embodiments of the described technologies are capable of reading a text sequence that include at least one word; extracting model input data from the text sequence, where the model input data includes, for each word of the text sequence, segment data and non-segment data; using a first machine learning model and at least one second machine learning model, generating, for each word of the text sequence, a multi-level feature set; outputting, by a third machine learning model, in response to input to the third machine learning model of the multi-level feature set, a tagged version of the text sequence; executing a search based at least in part on the tagged version of the text sequence.

Abstract: A system and method for inferring appropriate courses for recommendation based on member characteristics is disclosed. A social networking system receives a request for recommended courses, wherein the request is associated with a member of the social networking system. The social networking system identifies a group of members who are similar to the first member. The social networking system creates a list of recently learned skills by members of the group of members similar to the member. For a particular skill in the list of skills, the social networking system determines whether the member possesses the particular skill. In accordance with a determination that the member does not possess the particular skill, the social networking system identifies at least one course that teaches the particular skill from a list of courses. The social networking system transmits the identified course to the client device for display as a recommended course.

Abstract: Techniques for inferring a specific skill associated with a job posting are described. In an example, disclosed is a system that selects, from a jobs database, a specific job posting from a plurality of job postings. Additionally, job applicants for the specific job posting can be determined using indicators in the profile data of members. Moreover, a set of skills associated with the job applicants can be obtained. Furthermore, a percentage of the job applicants having a specific skill from the set of skills can be determined using the profile data of the job applicants. Subsequently, a confidence score of the specific skill being associated with the specific job posting can be calculated based on the percentage of the job applicants having the specific skill. A user interface can display a presentation of the specific job posting to a first member when the confidence score transgresses a predetermined score.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains a set of member features associated with a member of a social network and a set of attribute features associated with a set of member attributes. Next, the system analyzes the member features and the attribute features to predict a propensity of the member to accept recommendations of the member attributes as profile edits to a member profile of the member. The system then uses the predicted propensity to output a subset of the member attributes as recommended profile edits to the member.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system identifies skills that are trending within a social network based on usage features associated with usage of the skills in the social network. Next, the system matches one or more of the skills to member features for a member of the social network. The system then outputs a recommendation of the skill(s) to the member.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains job histories for members of the social network. Next, the system aggregates a set of job transitions in the job histories to obtain a set of job transition trends associated with the members. The system then matches a job transition trend in the set of job transition trends to member features for a member of the social network. Finally, the system outputs the job transition trend as a recommendation for advancing a career of the member.

Abstract: Among other things, embodiments of the present disclosure discussed herein may be used to analyze the online social network profiles of users of the social network and generate customized summaries of the profiles. Among other things, the embodiments of the present disclosure help quickly and efficiently generate an intuitive and personalized summary of a user's profile, even where a user's profile contains a relatively lengthy amount of content.

Abstract: Among other things, embodiments of the present disclosure discussed herein may be used to analyze the online social network profiles of members of the social network and identify new content items. The system can also identify similarities between newly-identified content items and existing content items in member profiles to alert members to the new content items for possible inclusion in their profiles.

Abstract: Systems and methods for identifying appropriate course recommendations are disclosed. A system receives a request for recommended courses and accesses a plurality of course records to determine whether a sufficient number of courses that teach the skill of interest are available. In accordance with a determination that a sufficient number of courses that teach the skill of interest are not available, the system generates skill attribute vectors for a skill of interest and a plurality of other skills and ranks the plurality of other skills based on the distance between the skill attribute for the skill of interest and the plurality of other skills. The system selects a skill based on the rankings. The system identifies at least one course that teaches the selected skill and transmits a course recommendation for the identified course to a client system for presentation.

Abstract: Among other things, embodiments of the present disclosure discussed herein may be used to analyze the online social network profiles of users of the social network and generate customized summaries of the profiles. Among other things, the embodiments of the present disclosure help quickly and efficiently generate an intuitive and personalized summary of a user's profile, even where a user's profile contains a relatively lengthy amount of content.

Abstract: A system and method for inferring appropriate courses for recommendation based on member characteristics is disclosed. A social networking system receives a request for recommended courses, wherein the request is associated with a member of the social networking system. The social networking system identifies a group of members who are similar to the first member. The social networking system creates a list of recently learned skills by members of the group of members similar to the member. For a particular skill in the list of skills, the social networking system determines whether the member possesses the particular skill. In accordance with a determination that the member does not possess the particular skill, the social networking system identifies at least one course that teaches the particular skill from a list of courses. The social networking system transmits the identified course to the client device for display as a recommended course.

Abstract: Techniques for associating a specific skill with a job posting are described. In an example, disclosed is a system having a standardization database and a skills database. The system can extract textual features from a job posting, and select a specific skill for the job posting from a plurality of skills. Moreover, a job title for the job posting can be selected from a plurality of standardized job titles. Furthermore, an affinity score can be accessed for specific skill based on the selected job title. The system can determine a skill frequency score associated with the specific skill. The system can calculate a confidence score of the specific skill based on the textual features, the affinity score, and the skill frequency score. Subsequently, the system can store, in the skills database, an association of the specific skill with the job posting when the confidence score is above a predetermined threshold.

Abstract: Techniques for inferring a specific skill associated with a job posting are described. In an example, disclosed is a system that selects, from a jobs database, a specific job posting from a plurality of job postings. Additionally, job applicants for the specific job posting can be determined using indicators in the profile data of members. Moreover, a set of skills associated with the job applicants can be obtained. Furthermore, a percentage of the job applicants having a specific skill from the set of skills can be determined using the profile data of the job applicants. Subsequently, a confidence score of the specific skill being associated with the specific job posting can be calculated based on the percentage of the job applicants having the specific skill. A user interface can display a presentation of the specific job posting to a first member when the confidence score transgresses a predetermined score.

Abstract: Systems and methods for analyzing job listing data and member profile data to identify in demand skills is disclosed. A computer system receives a request for recommended job listings from a client device. The system accesses a plurality of job listings from a database. The system parses each of the job listings of the plurality of job listings to identify a list of skills required by each job listing. The system accesses a plurality of member profiles. The system analyzes the plurality of member profiles to extract a list of skills from each member profile. For a particular skill in the list of skills, the system calculates a first number of job listings requiring the particular skill and a first number of members who possess the particular skill. The system determines a skill gap value for the particular skill based on the number of job listings requiring that particular skill and the number of members who possess that particular skill.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains user feedback associated with recommending a set of member attributes as profile edits to a set of members in a social network. Next, the system analyzes the user feedback to determine a set of acceptance rates of the member attributes. The system then uses the acceptance rates to update a taxonomy of the member attributes for use in improving recommendations of the member attributes to the members.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains a set of member features associated with a member of a social network and a set of attribute features associated with a set of member attributes. Next, the system analyzes the member features and the attribute features to predict a propensity of the member to accept recommendations of the member attributes as profile edits to a member profile of the member. The system then uses the predicted propensity to output a subset of the member attributes as recommended profile edits to the member.