个性化新闻推荐算法研究综述
摘要
获取新闻资讯的重要方式,因此,如何提升新闻推荐算法的准确度是研究者们主要关注的问题之一。本文介绍了新
闻推荐算法的研究进展,对基于内容的推荐、协同过滤推荐、混合推荐和基于深度学习的推荐算法进行了介绍,总
结了方法特点,并介绍了其中优秀方法模型,另外还介绍了新闻推荐算法常用的评价指标,并分析了新闻推荐算法
面临的问题。
关键词
全文:
PDF参考
[1]SAMARINAS C,ZAFEIRIOU S. Personalized high
quality news rec- ommendations using word embeddings and
text classification models [Z]. EasyChair,2019.
[2]P. Melville and V. Sindhwani,“Recommender
systems,”in Encyclopedia of Machine Learning and Data
Mining. Boston, MA, USA: Springer, 2011, pp. 829-838.
[3]B. Sarwar, G. Karypis, J. Konstan, and J. Reidl,
“Item-based collaborative filtering recommendation
algorithms,”in Proc. 10th Int. Conf. World Wide Web
(WWW), 2001, pp. 285-295.
[4]H. L. Borges and A. C. Lorena,“A survey on
recommender systems for news data,”in Smart Information
and Knowledge Management. Berlin, Germany: Springer,
2010, pp. 129-151.
[5]S. Athalye,“Recommendation system for news
reader,”M.S. thesis, Fac. Comput. Sci., San Jose State Univ.,
San Jose, CA, USA, 2013, doi:10.31979/etd.xn48-6q4.
[6]M. Gorzin, M. Hosseinpoorpia, F.-A. Parand, and S.
A. Madine,“A survey on ordered weighted averaging operators
and their application in recommender systems,”in Proc. 8th Int.
Conf. Inf. Knowl. Technol. (IKT), Sep. 2016, pp. 211-215.
[7]F. Graber, H. Malberg, S. Zaunseder, S. Beckert, D.
Kuster, J. Schmitt, S. A. Klinik, and P. Fur Dermatologie,
“Application of recommender system methods for therapy
decision support,”in Proc. IEEE 18th Int. Conf. e-Health
Netw., Appl. Services (Healthcom), Sep. 2016, pp. 1-6.
[8]C. Lin, R. Xie, L. Li, Z. Huang, and T. Li,
“PRemiSE: Personalized news recommendation via implicit
social experts,”in Proc. 21st ACM Int. Conf. Inf. Knowl.
Manage. (CIKM), 2012, pp. 1607-1611.
[9]G. Linden, B. Smith, and J. York,“Amazon.com
recommendations: Itemto-item collaborative filtering,”IEEE
Internet Comput., vol. 7, no. 1, pp. 76-80, Jan. 2003.
[10]R. Burke,“Hybrid recommender systems: Survey
and experiments,”User Model. User-Adapted Interact., vol.
12, no. 4, pp. 331-370, Nov. 2002.
[11]P. Melville, R. J. Mooney, and R. Nagarajan,
“Content-boosted collaborative filtering for improved
recommendations,”in Proc. AAAI/IAAI, 2002, pp. 187-192.
[12]Zhu Q , Zhou X , Song Z ,et al.DAN: Deep Attention
Neural Network for News Recommendation[C]//2019.
DOI:10.1609/aaai.v33i01.33015973.
[13 ]An M , Wu F , Wu C ,et al.Neu ral New s
Recommendation with Long- and Short-term User
Representations[J]. 2019.DOI:10.18653/v1/P19-1033.
[14]WU C,WU F,GE S,et al. Neural news
recommendation with multi-head self-attention[C]∥Proceed_xfffe_ings of the 2019 Conference on Empirical Methods in Natural
Language Processing and the 9th International Joint Conference
on Natural Language Processing(EMNLP-IJCNLP),2019:
91
计算机与通信进展 | 第2卷/第5期
Advances in Computers and Communications
6389-6394.
[15]Wu C , Wu F , An M ,et al.NPA: Neural News
Recommendation with Personalized Attention[J].arXiv e-prints,
2019.
[16]Zhu Q , Zhou X , Song Z ,et al.DAN: Deep Attention
Neural Network for News Recommendation[C]//2019.
DOI:10.1609/aaai.v33i01.33015973.
[17]Li J, Zhu J, Bi Q, et al. MINER: Multi-interest
matching network for news recommendation[C]//Findings
of the Association for Computational Linguistics: ACL 2022.
2022: 343-352.
[18]Sertkan M, Althammer S, Hofstätter S, et al.
Diversifying Sentiments in News Recommendation[C]//
Perspectives@ RecSys. 2022.
[19]翁海瑞,林穗,何立健.基于内容推荐与时间函
数结合的新闻推荐算法 [J].计算机与数字工程,2020,48
(12):2973-2977.
[20]王曙燕,巩婧怡.融合长短时序与文本分类的新闻
推荐模型 [J].西安邮电大学学报,2023,28(3):82-87.
[21]万梅,曹琳.基于神经网络嵌入和动态社交的新
闻推荐算法 [J].计算机应用与软件,2021,38(7):258-
264,331.
[22]张译丹.基于混合新闻推荐的微服务工具应用
研 究 [D].中 国 传 媒 大 学,2023.DOI:10.27483/d.cnki.
gbjgc.2023.000069.
[23]李梅.基于协同过滤的新闻推荐算法研究 [J].电
脑知识与技术,2022,18(34):51-53.DOI:10.14004/
j.cnki.ckt.2022.2228.
Refbacks
- 当前没有refback。