Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Jobs Optimization Engine. The Jobs Optimization Engine accesses at least one respective apply probability that corresponds to a given job post from a plurality of job posts, each respective apply probability represents a likelihood that the target member account will apply to the given job post. The Jobs Optimization Engine determines, according to an input context and the at least one respective apply probability, a respective boost factor for each given job post based on including the given job post in a select listing of job posts that satisfies (i) a job post diversity requirement and (ii) a potential revenue target that can be generated by the select listing of job posts.

Abstract: Various embodiments described herein provide for systems and methods for using a machine-learning model to rank job search results based on the similarity of the job title of each job search result and a job search query that produces the job search results. According to some embodiments, the machine-learning model comprises a word-embedding machine-learning model that maps a word to a vector.

Abstract: A trained search system can be configured to retrieve a candidate subset of results, where the trained search system uses data extracted from a machine learning scheme. The machine learning scheme can be trained to identify results that are ranked by a computationally expensive algorithm, such as a ranking algorithm. When a query is received, the trained search system can he used to retrieve results instead of applying the computationally expensive ranking algorithm.

Abstract: Methods, systems, and computer programs are presented for expanding a job search that includes an industry by adding other similar industries. A method accesses, by a social networking server, a plurality of job applications, with each job application being submitted by a member for a job in a company, the member and the job having a respective industry from a plurality of industries. Semantic analysis of the job applications is performed by a machine-learning program to identify similarity coefficients among the plurality of industries. A job search query is received from a first member, the job search query including a query industry, and the job search query is expanded with industries that are similar to the query industry. The social networking server executes the expanded job search query to generate a plurality of job results. Presentation is provided on a display of one or more of the top job results.

Abstract: Methods, systems, and computer programs are presented for expanding a job search that includes an industry by adding other similar industries. A method identifies job titles of members in a social network and performs, utilizing a machine-learning program, semantic analysis of the job titles to identify similarity coefficients among the job titles. The machine-learning program utilizes social network data to identify the similarity coefficients. Further, the method includes an operation for receiving a job search query, from a first member, including a query job title, and for expanding the job search query with job titles that are similar to the query job title. The method further includes operations for executing the expanded job search query to generate a plurality of job results, and for causing presentation on a display of one or more of the top job results.

Abstract: Methods and systems for selecting candidate content for insertion into a content presentation to generate tailored user interface screens are described. According to various embodiments, the system receives a set of publication data including a plurality of content pages with content elements. The system determines a set of content divisions among the content pages and one or more insertion points corresponding to one or more content divisions. The system determines a set of candidate insertion content based on the set of content elements and the insertion points. The system causes presentation of the set of publication data including the plurality of content pages. Upon presentation of a content page proximate to an insertion point, the system selects a candidate insertion content item for insertion into the insertion point and causes presentation of the candidate insertion content during presentation of the set of publication data.

Abstract: A system and method for inferring service providers are provided. In example embodiments, member data of members of a social networking service is accessed. From the member data, it is inferred that a particular member among the members of the social networking service is a freelancer member. A service request that the freelancer member is capable of fulfilling is identified based on a service request skill associated with the service request and a freelancer skill of the freelancer member. An option for the freelancer member to fulfill the service request is presented on a user interface of a user device of the freelancer member.

Abstract: A system and method for inferring service opportunities are provided. In example embodiments, a member event associated with a particular member of a social networking service is detected. In response to detecting the member event, a service request for a particular service is inferred based on the member event. A provider member capable of fulfilling the inferred service request is identified among members of the social networking service. A match score for each of the identified provider members is calculated. The identified provider members are ranked according to the calculated match score. At least a portion of the ranked identified provider members are presented on a user interface.

Abstract: In an example embodiment, a method is provided to calculate a distance for a first member of a social networking service and a job opening, which indicates the likelihood that the first member will obtain the job. The distance is calculated by applying one or more policies to member profiles of members who applied for similar jobs to obtain a hypothetical perfect candidate for the job. The member's profile is then automatically compared to the hypothetical perfect candidate profile to calculate the distance.

Abstract: A member profile including a vector containing a field for each of a plurality of skills and a rating of one or more of the skills in the vector for a member of a social networking service is obtained. A first distance indicating a vector distance between the vector of the member profile and a vector of a hypothetical member profile representing the perfect job candidate is obtained. A hypothetical member profile for the member is created by combining the vector of the member profile with the indication of how each of the one or more skills is improved through taking the course from course information. A second distance between the member and the hypothetical perfect candidate for the job is obtained, and the difference between the first distance and the second distance is calculated to determine an estimate of how much the course will increase the member's job chances.

Abstract: In an example embodiment, a method is provided where information regarding a member of a social networking service and a job opening are obtained. Then information about a plurality of courses available for the member to take is obtained, the information including cost, time, and a vector including, for each of a plurality of skills identified in a member profile of the member, an effect of taking the corresponding course. A subset selection algorithm is then used to select an optimal combination of courses selected from the plurality of courses, based on minimizing cost and time while maximizing cumulative increase in odds of the member successfully obtaining the job opening from taking the selected courses.