Papers
2008
- M. Meiss, F. Menczer, S. Fortunato, A. Flammini, and A. Vespignani. Ranking Web sites with real user traffic. Proc. 1st Intl. Web Search and Data Mining Conference, Stanford, CA, 2008.
- M. Meiss, F. Menczer, and A. Vespignani. Structural analysis of behavioral networks from the Internet. Accepted to Journal of Physics A: Mathematical and Theoretical, publication pending.
2007
- M. Meiss, F. Menczer, and A. Vespignani. A framework for analysis of anonymized network flow data. National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Baltimore, MD, Oct. 2007. (Accepted as poster.)
- M. Meiss. Race Pharming. In Phishing and Counter-Measures: Understanding the Increasing Problem of Electronic Theft and Identitity, Wiley, 2007.
2006
- Katy Börner, Shashikant Penumarthy, Mark Meiss, and Weimao Ke. Mapping the diffusion of scholarly knowledge among major U.S. research institutions. In Scientometrics 68(3): 415-426, 2006.
2005
- Colin Murray, Weimao Ke, Hana Milanov, Mark Meiss, Sharavan Rajagopal, and Katy Börner Geographical Visualization of Technology Data in the US. IEEE InfoVis 2005 Contest Submission.
- M. Meiss, F. Menczer, A. Vespignani. On the lack of typical behavior in the global Web traffic network. Proc. WWW2005
Other
I've also placed here a brief selection of my previous efforts for graduate-level courses and the ANML.
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Standards-Based
Discovery of Switched Ethernet Topology
This paper describes an algorithm for using SNMP in conjunction with vendor-neutral MIBs to reliably determine the topology of a switched Ethernet network.
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A Unique Identifier
for Network Hosts
This brief article describes a method of constructing a one-way hash that reflects the physical configuration of a network device.
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Tsunami: A High-Speed
Rate-Controlled Protocol for File Transfer
Tsunami is a file transfer protocol that is tolerant of low-level packet loss and high-latency networks.
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Miner/Event
Miner/Event was a class project for a course in Web data mining. It uses the Web as an unreliable, high-latency database for probabilistically associating calendar years with query terms.