Òscar Celma
Information Systems · 2008–2010
A researcher in the Science corpus: 4 papers; trusts 37 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 29 citations into it
- Management Science and Operations Research — 17 citations into it
- Computer Vision and Pattern Recognition — 15 citations into it; #14,367 of 21,575 by trust here, #18,782 by citations
- Statistical and Nonlinear Physics — 14 citations into it; #6,710 of 10,127 by trust here, #7,402 by citations
- Artificial Intelligence — 13 citations into it; #23,219 of 35,345 by trust here, #31,361 by citations
- Computer Networks and Communications — 8 citations into it
- Signal Processing — 8 citations into it; #3,037 of 7,572 by trust here, #4,373 by citations
- Recommender Systems — 7 citations into it
Whom Òscar Celma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- George Karypis
- Sean P. Meyn
- Jonathan L. Herlocker
- Marko Balabanovic
- Daniel D. Lee
- P. Paatero
- J. Konstan
- J. Breese
- Richard L. Tweedie
Who trusts Òscar Celma overall
- Marius Kaminskas
- Yang Li
- Allison June-Barlow Chaney
- Suvash Sedhain
- Balázs Hidasi
- Derek G. Bridge
- Noam Koenigstein
- Nan Du
- Brandon M Stewart
- Aditya Krishna Menon
Papers from Òscar Celma's perspective
Ordered by how strongly the researchers Òscar Celma trusts endorse each paper. Same corpus, a different order for every researcher.
- Empirical Analysis of Predictive Algorithms for Collaborative Filtering
- An open architecture for collaborative filtering of netnews
- Fab: content-based, collaborative recommendation
- Item-based collaborative filtering recommendation algorithms
- The Structure and Function of Complex Networks
- Evaluating collaborative filtering recommender systems
- Using collaborative filtering to weave an information tapestry
- Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
- An algorithm for suffix stripping
- Relevance feedback in information retrieval
Their papers
- The Long Tail in Recommender Systems (2010) — 29 citations
- Music Recommendation and Discovery - The Long Tail, Long Fail, and Long Play in the Digital Music Space (2010) — 446 citations
- From hits to niches?: or how popular artists can bias music recommendation and discovery (2008) — 206 citations
- Music recommendation and discovery in the long tail (2008) — 345 citations