  This paper describes the approach of the THUIR team at the WSDM Cup 2023
Pre-training for Web Search task. This task requires the participant to rank
the relevant documents for each query. We propose a new data pre-processing
method and conduct pre-training and fine-tuning with the processed data.
Moreover, we extract statistical, axiomatic, and semantic features to enhance
the ranking performance. After the feature extraction, diverse learning-to-rank
models are employed to merge those features. The experimental results show the
superiority of our proposal. We finally achieve second place in this
competition.
