Papers Job classification
“Job classification” 태그가 달린 논문 5편 · 필터 해제
Forecasting Application Counts in Talent Acquisition Platforms: Harnessing Multimodal Signals using LMs
As recruitment and talent acquisition have become more and more competitive, recruitment firms have become more sophisticated in using machine learning (ML) methodologies for optimizing their day to day activities. But, …
Job classificationTime SeriesTime Series ForecastingNasdaq-100 Companies' Hiring Insights: A Topic-based Classification Approach to the Labor Market
The emergence of new and disruptive technologies makes the economy and labor market more unstable. To overcome this kind of uncertainty and to make the labor market more comprehensible, we must employ labor market intell…
Job classificationMarketingLarge Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification
This case study investigates the task of job classification in a real-world setting, where the goal is to determine whether an English-language job posting is appropriate for a graduate or entry-level position. We explor…
Job classificationPrompt Engineeringtext-classificationText Classification+2Flexible Job Classification with Zero-Shot Learning
Using a taxonomy to organize information requires classifying objects (documents, images, etc) with appropriate taxonomic classes. The flexible nature of zero-shot learning is appealing for this task because it allows cl…
ClassificationDocument ClassificationJob classificationRecommendation Systems+2Job Prediction: From Deep Neural Network Models to Applications
Determining the job is suitable for a student or a person looking for work based on their job's descriptions such as knowledge and skills that are difficult, as well as how employers must find ways to choose the candidat…
Job classificationJob PredictionWord Embeddings