Codes for paper: Wenhui Yu, Xiao Lin, Junfeng Ge, Wenwu Ou, and Zheng Qin. 2020. Semisupervised Collaborative Filtering by Text-enhanced Domain Adaptation. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '20), August 23-27, 2020, Virtual Event, CA, USA. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3394486.3403264 This project is for our model TMN, TCF, and TDAR. * Environment: Python 3.6.8 :: Anaconda, Inc. * Libraries: tensorflow 1.12.0 numpy 1.16.4 pandas 0.18.1 openpyxl 2.3.2 xlrd 1.0.0 xlutils 2.0.0 Please follow the steps below: 1. Download datasets and text features: https://drive.google.com/open?id=1Kk2S3JtEf9LHKpMPbrXL2KxbnVzl6f0f https://pan.baidu.com/s/1jVQV5Vyin9rlxWT0xb57Dg (password: 76af) You can choose one of these two URLs for downloading. Download and unzip TDAR_dataset.zip and use it to replace the folder dataset in our project. 2. MF, TMN, and TCF are in folder 2.review2vec. Running file _main.py in 2.review2vec. If you want to save the embeddings, set IF_SAVE_EMB in params.py as 1 (set _SAVE_EMB as 1 only if you are sure to save the embeddings, or the previous embeddings will be overwritten). 3. TDAR is in folder 3.tranfer_rec. Running file _main.py in 3.tranfer_rec. 4. Process the results with result_collection.