Copyright (c) 2023 MaiMemo, Inc. MIT License.
SSP-MMC-Plus is the extended version of SSP-MMC, a spaced repetition scheduling algorithm used to help learners remember more words in MaiMemo, a language learning application in China.
This repository contains a public release of the data and code used for several experiments in the following paper (which introduces SSP-MMC-Plus):
J. Su, J. Ye, L. Nie, Y. Cao and Y. Chen, "Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory," in IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2023.3251721.
The paper is a substantial extension of our previous conference paper A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling (free access).
When using this dataset and/or code, please cite this publication. A BibTeX record is:
@ARTICLE{10059206,
author={Su, Jingyong and Ye, Junyao and Nie, Liqiang and Cao, Yilong and Chen, Yongyong},
journal={IEEE Transactions on Knowledge and Data Engineering},
title={Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory},
year={2023},
volume={35},
number={10},
pages={10085-10097},
doi={10.1109/TKDE.2023.3251721}}
The dataset is available on Dataverse (1.6 GB). This is a 7zipped TSV file containing our experiments' 220 million MaiMemo student memory behavior logs.
The columns are as follows:
u - student user ID who reviewed the word (anonymized)
w - spelling of the word
i - total times the user has reviewed the word
d - difficulty of the word
t_history - interval sequence of the historic reviews
r_history - recall sequence of the historic reviews
delta_t - time elapsed from the last review
r - result of the review
p_recall - probability of recall
total_cnt - number of users who did the same memory behavior