Javier Parapar

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 6 citations into it; #33,190 of 35,345 by trust here, #32,362 by citations
• Information Systems — 6 citations into it
• Information Retrieval & Search — 5 citations into it; #956 of 1,022 by trust here, #966 by citations

Whom Javier Parapar trusts overall

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

1. Ellen M. Voorhees
2. Richard S. Sutton
3. J. Aslam
4. Andrew Barto

Who trusts Javier Parapar overall

1. James Allan

Papers from Javier Parapar's perspective

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

1. Some aspects of the sequential design of experiments
2. Reinforcement Learning: An Introduction
3. Information retrieval system evaluation: effort, sensitivity, and reliability
4. Finite-time Analysis of the Multiarmed Bandit Problem
5. The Philosophy of Information Retrieval Evaluation
6. Bias and the limits of pooling for large collections
7. Rank-biased precision for measurement of retrieval effectiveness
8. Learning diverse rankings with multi-armed bandits
9. Interactively optimizing information retrieval systems as a dueling bandits problem
10. Models for metasearch (Annual International ACM SIGIR Conference on Research and Development in Information Retrieval)

Their papers

• Feeling lucky?: multi-armed bandits for ordering judgements in pooling-based evaluation (2016) — 76 citations