Earticle

초록

영어

As a massive number of real-time news makes it difficult for users to find their preferred news, various news recommender systems have been actively proposed in the research field. With the two popular real-world datasets in a news domain, Adressa and MIND, we compare the four state-of-the-art news recommendation methods (i.e., NRMS, LSTUR, NAML, and CNE-SUE) in terms of accuracy. Also, we investigate the strengths and weaknesses of news recommendation methods depending on datasets or metrics.

목차

Abstract
I. INTRODUCTION
II. NEWS RECOMMENATION METHODS
III. EMPIRICAL EVALUATION
A. Experimental Setup
B. Experimental Result
IV. CONCLUSION
REFERENCES

저자

• Hong-Kyun Bae [ Department of Computer Science Hanyang University ]
• Jeewon Ahn [ Department of Computer Science Hanyang University ]
• Sang-Wook Kim [ Department of Computer Science Hanyang University ] Corresponding Author

참고문헌