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re-implementation of ConvMF+ (RecSys'16) in TensorFlow with even better performance

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ConvMF

re-implementation of ConvMF+ (RecSys'16) in TensorFlow with even better performance

Our implementatation achieves 0.848 in terms of RMSE (check the log.txt) on the ML-1M dataset provided by the authors while their reported result is only 0.8549.

Each line in the input text is formatted as:

user::item::rating::word1 word2 word3

Example:

BCB7302F3A2AD466E27937439CF8AF8C::305921::5::ask for a view of the harbour ! 14th floor was very quiet . come to the kowloon side .

Original paper:

Kim, Donghyun, et al. "Convolutional matrix factorization for document context-aware recommendation." Proceedings of the 10th ACM Conference on Recommender Systems. ACM, 2016.

We appreciate it if you cite our paper when using the code:

@inproceedings{RSBD19-CCANN, title = {Context-aware Co-Attention Neural Network for Service Recommendations}, author = {Li, Lei and Dong, Ruihai and Chen, Li}, booktitle = {Proceedings of ICDE'19 Workshop on Recommender Systems with Big Data}, year = {2019}, organization = {IEEE} }

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re-implementation of ConvMF+ (RecSys'16) in TensorFlow with even better performance

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