Jesús Bobadilla
Information Systems · 2010–2013
A researcher in the Science corpus: 3 papers; trusts 23 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 77 citations into it; #3,934 of 8,771 by trust here, #1,740 by citations
- Computer Vision and Pattern Recognition — 26 citations into it; #17,698 of 21,575 by trust here, #20,271 by citations
- Artificial Intelligence — 24 citations into it
- Management Science and Operations Research — 18 citations into it; #7,263 of 11,946 by trust here, #8,469 by citations
- Signal Processing — 18 citations into it; #6,261 of 7,572 by trust here, #1,820 by citations
- Computer Networks and Communications — 11 citations into it
- Marketing — 11 citations into it
- Recommender Systems — 11 citations into it; #177 of 233 by trust here, #108 by citations
Whom Jesús Bobadilla trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jonathan L. Herlocker
- Gediminas Adomavicius
- J. Breese
- J. Konstan
- John Riedl
- Hyung Jun Ahn
- Badrul Munir Sarwar
- William W. Cohen
- Michael J. Pazzani
- Robin D. Burke
Who trusts Jesús Bobadilla overall
- Hao Wang
- Fernando Ortega
- John K. Tarus
- Guolei Yang
- Folasade Olubusola Isinkaye
- Antonio Hernando
- Kun Zhou
- Wen Zhang
- Muhammad Ammad-ud-din
- Wu-Jun Li
Papers from Jesús Bobadilla's perspective
Ordered by how strongly the researchers Jesús Bobadilla trusts endorse each paper. Same corpus, a different order for every researcher.
- Empirical Analysis of Predictive Algorithms for Collaborative Filtering
- Item-based collaborative filtering recommendation algorithms
- Evaluating collaborative filtering recommender systems
- An algorithmic framework for performing collaborative filtering
- Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
- Explaining collaborative filtering recommendations
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Content-boosted collaborative filtering for improved recommendations
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Their papers
- A collaborative filtering approach to mitigate the new user cold start problem (2012) — 521 citations
- A new collaborative filtering metric that improves the behavior of recommender systems (2010) — 316 citations
- Recommender systems survey (2013) — 3,186 citations