Pablo Castells

Information Systems · 2005–2022

A researcher in the Science corpus: 6 papers; trusts 38 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 65 citations into it; #2,224 of 8,771 by trust here, #2,741 by citations
• Artificial Intelligence — 48 citations into it; #19,399 of 35,345 by trust here, #24,417 by citations
• Management Science and Operations Research — 37 citations into it; #4,240 of 11,946 by trust here, #3,705 by citations
• Information Retrieval & Search — 28 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Computer Networks and Communications — 15 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Signal Processing — 13 citations into it

Whom Pablo Castells trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yehuda Koren
2. Alistair Moffat
3. Filip Radlinski
4. Olivier Chapelle
5. Atanas Kiryakov
6. Siegfried Handschuh
7. Borislav Popov
8. Jaime G. Carbonell
9. Sean M. McNee
10. Justin Zobel

Who trusts Pablo Castells overall

1. Marius Kaminskas
2. Himanshu Jain
3. Pedro G. Campos
4. Derek G. Bridge
5. Faezeh Ensan
6. Mozhgan Karimi
7. Tinghuai Ma

Papers from Pablo Castells's perspective

Ordered by how strongly the researchers Pablo Castells trusts endorse each paper. Same corpus, a different order for every researcher.

1. Evaluating collaborative filtering recommender systems
2. Empirical Analysis of Predictive Algorithms for Collaborative Filtering
3. Indexing by Latent Semantic Analysis
4. Rank-biased precision for measurement of retrieval effectiveness
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Semantic Annotation, Indexing, and Retrieval (International Workshop on the Semantic Web)
9. ImageNet classification with deep convolutional neural networks
10. Item-based collaborative filtering recommendation algorithms

Their papers

• Human Preferences as Dueling Bandits (2022) — 22 citations
• Rank and relevance in novelty and diversity metrics for recommender systems (2011) — 755 citations
• Novelty and Diversity in Recommender Systems (2015) — 399 citations
• Precision-oriented evaluation of recommender systems: an algorithmic comparison (2011) — 226 citations
• An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval (2007) — 516 citations
• An Ontology-Based Information Retrieval Model (2005) — 295 citations