The analysis and design of the job recommendation model based on GBRT and time factors

In this paper, we first give a comprehensive summary of models and algorithms applied in three online job recommender systems and point out the advantages and disadvantages of these models. Then we introduce a job recommendation model based on Gradient Boosting Regression Tree and time factors (T-GBRT). The T-GBRT model aggregates the time factors into the GBRT to predict personal preferences and adds time factor weight to topK rankings, with a neighbor based filtering trick in reducing the amount of calculation. At the end of the paper, the model performs the best in the experiment with four criterions, comparing to other three models, which proves the efficiency of the new model.