Abstract: Method and apparatus are disclosed for classification of job titles via machine learning. An example system includes memory configured to store a convolutional neural network (CNN). The CNN includes a character-title partial-CNN, a word-title partial-CNN, a description CNN, and at least one fully-connected layer. The example system also includes one or more processors configured to apply the character-title partial-CNN to a title to generate a character-level feature, apply the word-title partial-CNN to the title to generate a first word-level feature, and apply the description partial-CNN to a description to generate a second word-level feature. The one or more processors are configured to generate a posting feature by concatenating the character-level feature, the first word-level feature, and the second word-level feature.

Abstract: Automated systems and methods for determining jobs, skills, and training recommendations are disclosed. An example system includes one or more processors of an employment website entity. The one or more processors are configured to extract job information and skill information from resumes in a resume database, generate a job transition graph based on the job information, generate a job-skill graph based on the job information and the skill information, and generate a skill re-occurrence graph based on the skill information. The one or more processors are configured to determine a jobs matrix by minimizing an objective function based on the job transition graph, the job-skill graph, and the skill re-occurrence graph. The one or more processors are configured to retrieve next job recommendations from the jobs matrix based on a the current job position of a candidate and present, via an employment app, the next-job recommendations for the candidate.

Abstract: Methods and apparatus are disclosed for location-based augmented reality for job seekers. An example system includes a mobile device and a remote server. The mobile device includes a camera to collect video and a processor configured to execute an employment app to generate, in real-time, a computer-generated layer that includes a balloon for each of the employment locations. The processor also is configured to execute the employment app to generate, in real-time, an augmented reality interface by overlaying the computer-generated layer onto the video. A display location and a display size for each of the balloons indicate the employment locations to the employment candidate. The mobile device includes a display to display the augmented reality interface. The remote server is configured to identify up to the predetermined number of the employment locations. Each of the employment locations corresponds with one or more employment postings.

Abstract: Method and apparatus are disclosed for automated resume and job posting creation with limited user-generated information. An example automated system includes a database and processor(s). The processor(s) are configured to obtain employment information for previous positions of a candidate via an employment app. For each of the previous positions, the processor(s) are configured to present a position interface; collect an employer name, a position title, a location, and a period of employment via the position interface; present a responsibilities interface that includes suggested responsibilities for the previous position; and collect, via the responsibilities interface, one or more selected responsibilities. The processor(s) are configured to retrieve, for each of the previous positions, the suggested responsibilities from the database based on the employer name, the position title, the location, and the period of employment.