Research And Implementation Of Job Recommendation System Integrating Sentiment Analysis

Job recommendation is widely used in major recruitment websites because it can quickly allow job seekers to find a job that suits them from a large amount of recruitment information.Currently,job recommendation is recommended based on the degree of match between the job and the job seeker,ignoring the influence of company on job applicants.Here on the basis of job recommendation in the computer field,combined with sentiment analysis technology,research and implementation of a job recommendation system incorporating sentiment analysis,and publish corporate factors into the job recommendation.The main work here is as follows:(1)Carry out demand analysis and feasibility analysis on the job recommendation system integrated with sentiment analysis,and design the system architecture,functional modules and database.The functional modules mainly include job management,resume management,evaluation of companies and job recommendation.The job recommendation is mainly implemented based on the proposed job recommendation algorithm integrated with sentiment analysis.(2)Propose a job recommendation algorithm that integrates sentiment analysis.After preprocessing and labeling the collected corporate comment texts,construct a corporate domain comment text data set,train a fine-tuned BERT model on this dataset to obtain the sentiment analysis model of corporate domain comment text,and formulate the corresponding rules to calculate the sentiment score of the enterprise.And then summarize the resume feature data and position feature data,divide them into structured data and unstructured data,and formulates the similarity calculation rules respectively to get the similarity value of the resume and the position.And finally,the corporate sentiment score and the similarity value of the resume and the position are linearly weighted to form the final position recommendation result.(3)The recommendation system with integrated sentiment analysis is developed using the front-end separation model,and after the system development is completed,the system functions and performance are tested to ensure the software quality.