William Webber

Information Systems · 2009–2013

A researcher in the Science corpus: 3 papers; trusts 21 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 27 citations into it; #2,738 of 8,771 by trust here, #2,471 by citations
• Artificial Intelligence — 25 citations into it; #30,099 of 35,345 by trust here, #19,873 by citations
• Information Retrieval & Search — 18 citations into it; #876 of 1,022 by trust here, #577 by citations
• Evaluation & Benchmarks — 10 citations into it; #2,582 of 3,147 by trust here, #2,369 by citations
• Statistics and Probability — 9 citations into it
• Natural Language Processing — 7 citations into it
• Computer Science Applications — 6 citations into it
• Management Science and Operations Research — 6 citations into it; #4,088 of 11,946 by trust here, #2,799 by citations

Whom William Webber trusts overall

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

1. Justin Zobel
2. Alistair Moffat
3. Ellen M. Voorhees
4. Ronald Fagin
5. Emine Yilmaz
6. Mark Sanderson
7. J. Aslam
8. Chengxiang Zhai
9. David D. Lewis
10. Maura R. Grossman

Who trusts William Webber overall

1. C. Clarke
2. Federico Bianchi
3. J. Shane Culpepper
4. Olga Zagovora
5. Jimmy J. Lin
6. Joel M. Mackenzie
7. Alexandra Vtyurina
8. Silvia Terragni
9. Mark D. Smucker
10. Roberto Ulloa

Papers from William Webber's perspective

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

1. Cumulated gain-based evaluation of IR techniques
2. Variations in relevance judgments and the measurement of retrieval effectiveness
3. Information retrieval system evaluation: effort, sensitivity, and reliability
4. Comparing top k lists (ACM-SIAM Symposium on Discrete Algorithms)
5. Rank-biased precision for measurement of retrieval effectiveness
6. A comparison of statistical significance tests for information retrieval evaluation
7. How reliable are the results of large-scale information retrieval experiments?
8. A Markov random field model for term dependencies
9. A study of smoothing methods for language models applied to information retrieval
10. A statistical method for system evaluation using incomplete judgments

Their papers

• A similarity measure for indefinite rankings (2010) — 884 citations
• Improvements that don't add up: ad-hoc retrieval results since 1998 (2009) — 260 citations
• Information Retrieval for E-Discovery (2013) — 35 citations