Data Mining for Item Recommendation in MOBA Games

This repository contains the implementation of the Recommender System Based on Classifiers (Section 4.3). The models are based on neural networks, logistic regression, and decision trees.

Results

Original result from our paper:

Method	Precision	Recall	F1-Score	MAP	MRR
D Tree@1	0.65	0.17	0.27	0.64	0.64
Logit@1	0.67	0.18	0.28	0.67	0.67
ANN@1	0.71	0.19	0.30	0.71	0.71
D Tree@3	0.47	0.37	0.41	0.71	0.73
Logit@3	0.53	0.42	0.46	0.74	0.76
ANN@3	0.60	0.48	0.52	0.78	0.79
D Tree@6	0.32	0.50	0.38	0.69	0.75
Logit@6	0.37	0.59	0.43	0.71	0.78
ANN@6	0.44	0.69	0.53	0.74	0.81

Citation

If you find this repository useful for your research, please consider citing our paper:

@inproceedings{10.1145/3298689.3346986,
	author = {Araujo, Vladimir and Rios, Felipe and Parra, Denis},
	title = {Data Mining for Item Recommendation in MOBA Games},
	year = {2019},
	isbn = {9781450362436},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	url = {https://doi.org/10.1145/3298689.3346986},
	doi = {10.1145/3298689.3346986},
	booktitle = {Proceedings of the 13th ACM Conference on Recommender Systems},
	pages = {393–397},
	numpages = {5},
	keywords = {item recommendation, MOBA games, data mining},
	location = {Copenhagen, Denmark},
	series = {RecSys ’19}
}