Abstract: Techniques for improving the accuracy, relevancy, and efficiency of a computer system of an online service by providing a user interface to optimize a digital page of a user on the online service are disclosed herein. In some embodiments, a computer system identifies job postings published on an online service as corresponding to a type of job based on feature data of each one of the job postings, extracts phrases from the identified job postings based on a corresponding relevancy measurement and a corresponding diversity measurement for each one of the phrases, determines a corresponding section of a page of a user to suggest for placement of the extracted phrase using a placement classifier for each one of the extracted phrases, and generates a corresponding recommendation for the page based on the extracted phrase and the determined section of the extracted phrase for each one of the phrases.

Abstract: A skills classification system is configured to calculate, for a skill from the skills database, industry-specific probabilities for the industries associated with the skill. An industry-specific probability for an industry with respect to a skill is the probability of that skill being a required skill for a job associated with that industry. The skills classification system also calculates an industry-agnostic probability with respect to that same skill, which is the probability of the skill being a required skills for any job regardless of the industry. Based on the distance between the set of industry-specific probabilities for the industries associated with the skill and the industry-agnostic probability, the skills classification system calculates a score for the skill. This score is used to determine whether the skill should be tagged with a soft skill identifier or a hard skill identifier.

Abstract: Techniques for improving the accuracy, relevancy, and efficiency of a computer system of an online service by providing a user interface to optimize a digital page of a user on the online service are disclosed herein. In some embodiments, a computer system identifies job postings published on an online service as corresponding to a type of job based on feature data of each one of the job postings, extracts phrases from the identified job postings based on a corresponding relevancy measurement and a corresponding diversity measurement for each one of the phrases, determines a corresponding section of a page of a user to suggest for placement of the extracted phrase using a placement classifier for each one of the extracted phrases, and generates a corresponding recommendation for the page based on the extracted phrase and the determined section of the extracted phrase for each one of the phrases.

Abstract: The disclosed embodiments provide a system for performing adaptive interview preparation for candidates. During operation, the system obtains a graph-based representation of potential questions for a candidate during an interview. Next, the system receives an answer by the candidate to a first question included in the graph-based representation. The system then calculates similarities between the answer and a set of sample answers to the first question. Finally, the system selects a second question for presentation to the candidate in the interview based on a highest similarity of the answer to a sample answer in the set of sample answers and an edge between the first and second questions in the graph-based representation. The system further triggers presentation of the selected second question to the candidate.

Abstract: Provided is a method of configuring a network switch. A configuration file is allowed to be edited on a server. The compatibility of the configuration file with a network switch is validated on the server. The configuration file is encrypted and applied to the network switch.