Development of the Employment Recommendation System based on K-Means Improved Collaborative Filtering Algorithm
Pengying Wan · Atlantis Highlights in Computer Sciences/Atlantis highlights in computer sciences · 2023
With the massive expansion of higher education, the employment pressure of college graduates has increased dramatically.Meanwhile, graduates are unable to find their preferred positions from the massive and heterogeneous data, and are extremely disturbed by many irrelevant information while searching.To address the above problems, this paper proposes the development of an employment recommendation system based on K-means improved collaborative filtering recommendation algorithm.First, the job seeker and employment job data are collected and preprocessed to understand the characteristics of job seekers and job resources, then the job seeker behavior matrix is established, and similar users are clustered by K-means clustering algorithm, and in the clustering process, the distance between data is calculated by using Euclidean formula, and then the set of neighboring items is selected by improved similarity calculation to predict the job seeker rating and realize recommendation.The experiments show that the method has improved in precision, recall and F-score ratio to some extent.