Positive unlabeled learning for building recommender systems in a parliamentary setting-Reference-Cited by-同舟云学术

Positive unlabeled learning for building recommender systems in a parliamentary setting

Published:2018-04 Issue: Volume:433-434 Page:221-232
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

de Campos Luis M.,Fernández-Luna Juan M.,Huete Juan F.,Redondo-Expósito Luis

Funder

European Regional Development Fund

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference41 articles.

1. R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval, Addison-Wesley, 2011.

2. Information filtering and information retrieval: two sides of the same coin?;Belkin;Commun. ACM,1992

3. A learning agent for wireless news access;Billsus,2002

4. Recommender systems survey;Bobadilla;Knowl. Based Syst.,2013

5. Learning Bayesian classifiers from positive and unlabeled examples;Calvo;Pattern Recognit. Lett.,2007

Cited by 17 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. Examining the structure of MPs in the UK-China relationship using speech-word pair bipartite networks;Aslib Journal of Information Management;2024-03-29

2. A novel landslide susceptibility prediction framework based on contrastive loss;GIScience & Remote Sensing;2024-02-02

3. Disruptive Technologies for Parliaments: A Literature Review;Future Internet;2023-02-05

4. Automatic noise reduction of domain-specific bibliographic datasets using positive-unlabeled learning;Scientometrics;2022-12-17

5. A loss matrix-based alternating optimization method for sparse PU learning;Swarm and Evolutionary Computation;2022-12