Grenville J. Armitage

Artificial Intelligence · 2005–2008

A researcher in the Science corpus: 4 papers; trusts 27 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #6,384 of 35,345 by trust here, #9,465 by citations
• Computer Networks and Communications — 24 citations into it; #1,005 of 9,886 by trust here, #1,475 by citations
• Computer Vision and Pattern Recognition — 6 citations into it
• Hardware and Architecture — 5 citations into it; #77 of 1,551 by trust here, #223 by citations

Whom Grenville J. Armitage trusts overall

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

1. Andrew William Moore
2. Mark A. Hall
3. Subhabrata Sen
4. Sebastian Zander
5. Matthew Roughan
6. Thomas Karagiannis
7. Maria Halkidi
8. Konstantina (Dina) Papagiannaki
9. Oliver Spatscheck
10. Arthur P. Dempster

Who trusts Grenville J. Armitage overall

1. Jun Zhang
2. Thuy T. T. Nguyen
3. Anna L. Buczak
4. Alberto Dainotti
5. Hyunchul Kim
6. Yang Xiang
7. Manuel Lopez-Martin
8. K. Claffy
9. Nickolaos Koroniotis
10. Jeffrey Erman

Papers from Grenville J. Armitage's perspective

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

1. Toward the Accurate Identification of Network Applications (Passive and Active Network Measurement Conference)
2. Flow Clustering Using Machine Learning Techniques (Passive and Active Network Measurement Conference)
3. Accurate, scalable in-network identification of p2p traffic using application signatures (The Web Conference)
4. Internet traffic classification using bayesian analysis techniques (Measurement and Modeling of Computer Systems)
5. BLINC: multilevel traffic classification in the dark (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
6. The Transmission Control Protocol (The Industrial Information Technology Handbook)
7. Correlation-based Feature Selection for Machine Learning
8. Wrappers for Feature Subset Selection
9. A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification (CCRV)
10. Traffic classification through simple statistical fingerprinting (CCRV)

Their papers

• A survey of techniques for internet traffic classification using machine learning (2008) — 1,751 citations
• A survey of covert channels and countermeasures in computer network protocols (2007) — 588 citations
• A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification (2006) — 784 citations
• Automated traffic classification and application identification using machine learning (2005) — 583 citations