Attentional Matrix Factorization with Document-context awareness and Implicit API Relationship for Service Recommendation-Reference-Cited by-同舟云学术

Attentional Matrix Factorization with Document-context awareness and Implicit API Relationship for Service Recommendation

Published:2020-01-29 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Australasian Computer Science Week Multiconference
language:
Short-container-title:

Author:

Nguyen Mo¹,Yu Jian¹,Bai Quan²,Yongchareon Sira¹,Han Yanbo³

Affiliation:

1. Auckland University of Technology New Zealand

2. University of Tasmania Australia

3. North China University of Technology China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3373017.3373034

Reference19 articles.

1. Latent dirichlet allocation;Blei M;Journal of machine Learning research 3,2003

2. Jesús Bobadilla Fernando Ortega Antonio Hernando and Abraham Gutiérrez. 2013. Recommender systems survey. Knowledge-based systems 46 (2013) 109–132. Jesús Bobadilla Fernando Ortega Antonio Hernando and Abraham Gutiérrez. 2013. Recommender systems survey. Knowledge-based systems 46 (2013) 109–132.

3. Cscf: A mashup service recommendation approach based on content similarity and collaborative filtering;Buqing C;International Journal of Grid & Distributed Computing,2014

4. Attentive Collaborative Filtering

5. Yehuda Koren. 2010. Factor in the neighbors: Scalable and accurate collaborative filtering. ACM Transactions on Knowledge Discovery from Data (TKDD) 4 1(2010) 1. Yehuda Koren. 2010. Factor in the neighbors: Scalable and accurate collaborative filtering. ACM Transactions on Knowledge Discovery from Data (TKDD) 4 1(2010) 1.

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Iterative framework based on multi-task learning for service recommendation;Journal of Systems and Software;2024-01

2. RLISR: A Deep Reinforcement Learning Based Interactive Service Recommendation Model;IEEE Access;2024

3. API Recommendation For Mashup Creation: A Comprehensive Survey;The Computer Journal;2023-11-30

4. Towards machine-learning-driven effective mashup recommendations from big data in mobile networks and the Internet-of-Things;Digital Communications and Networks;2023-02

5. Plot-aware transformer for recommender systems;Electronic Research Archive;2023