dl-recommendation

KO | EN

gitlite — search

#ai #android #machine-learning #deep-learning #linux #nodejs #java #windows #awesome #vue #awesome-list #pytorch #ios #openai

dl-recommendation

(★ 12)

code for "Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations"

dl-recommendation 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
Here is the code and datasets to reproduce the experiment result in our paper "Deep Learning for Sequential Recommendation: Algorithms, InfluentialFactors, and Evaluations"
# Code
- **GRU4Rec** is the code to reproduce the result of basic GRU4Rec, sample size, sample alpha, loss function and data augmentation. 
- **GRU4Rec-with-dwell-time** is the code to reproduce the result of Dwell time.
- **GRU4Rec-with-knn** is the code to reproduce the result of KNN.
- **category-and-behavior** is the code to reproduce the result of P-GRU, C-GRU and B-GRU, GRU4Rec(behavior) and GRU4Rec(category).
- **attention-mechanism** is the code to reproduce the result of Attention mechanism.
- **user** is the code to reproduce the result of user representation(implicit, embedded and recurrent).
- **data_preprocess** is the preprocessing code for each dataset.
# Datasets
- **RSC15** http://www.kaggle.com/chadgostopp/recsys-challenge-2015
- **RSC19** http://www.recsyschallenge.com/2019/
- **LastFM** http://mir.dcs.gla.ac.uk/lastfm/
# Experiment result
Please go to https://docs.google.com/spreadsheets/d/1Qs5KKugzheDMFH3YLNoQl50Z3hxRPAvTaEYavGgb5sc/edit?usp=sharing to find more experiment results that we didn't report in the paper.

# Acknowledgement
- **GRU4Rec** is the original [Theano implementation](https://github.com/hidasib/GRU4Rec) GRU4Rec.
- **GRU4Rec-with-dwell-time** is modified based on the original [Theano implementation](https://github.com/hidasib/GRU4Rec) GRU4Rec.
- **GRU4Rec-with-knn** is the original code for paper "When Recurrent Neural Networks meet the Neighborhood for
Session-Based Recommendation" (http://bit.ly/2nfNldD).
- **category-and-behavior** is modified based on the [TensorFlow implementation](https://github.com/Songweiping/GRU4Rec_TensorFlow) GRU4Rec.
- **attention-mechanism** is modified based on the [Pytorch implementation](https://github.com/Wang-Shuo/Neural-Attentive-Session-Based-Recommendation-PyTorch) NARM.
- **user** Implicit and Embedded are modified based on the [TensorFlow implementation](https://github.com/Songweiping/GRU4Rec_TensorFlow) GRU4Rec.
Recurrent is the original code for HRNN (https://github.com/mquad/hgru4rec).

dl-recommendation

dl-recommendation 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

dl-recommendation

dl-recommendation 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README