VAST is a light-weight network library to support scalable peer-to-peer (P2P) virtual environment / virtual world applications such as Massively Multiplayer Online Games (MMOGs). It is based on the research of Voronoi-based Overlay Network (VON) published
This wiki is intended to provide a space for COMP4411 students (and staff) to share hints, tips, ideas, solutions and the like, related to the experimental robotics course.
In order to provide you with the most up-to-date information possible in the Computer Vision Homepage, we have created a special page for all the submissions that have yet to be filed in their appropriate sub-pages. From time to time, our filing process g
Discover more than one million documents from scholarly journals, magazines, conference proceedings, and other special publications from prestigious scientific societies and technical publishers.
The Trans-European Research and Education Networking Association offers a forum to collaborate, innovate and share knowledge in order to foster the development of Internet technology, infrastructure and services to be used by the research and education community.
PeerCQ is a peer-to-peer system for information monitoring on the web that uses CQs as its primitives to express information monitoring requests. The primary objective of the PeerCQ system is to build a decentralized Internet scale distributed system for monitoring information change on the web. The system is aimed to be highly scalable, self-organizing and support efficient and robust way of processing CQs.
My advisor is Prof. Ben Shneiderman, and I am a member of HCIL. My research is in the Information Visualization area of the Human-Computer Interaction field. My current research involves Network Visualization. I developed a tool called NVSS (see NVSS project page) to visualize netwoks (citation networks, food webs, social networks, etc.) using semantic substrates.
Graph mining refers to extracting knowledge from massive graphs. The data sets of telephone calls we see at AT&T can be viewed as a single graph, with several hundred million phone numbers as nodes, and calls between phone numbers as edges. It is a giant social network, like an internet connections graph or a rich citation network.
S. Das, D. Agrawal, and A. Abbadi. DaMoN '08: Proceedings of the 4th international workshop on Data management on new hardware, page 1--10. New York, NY, USA, ACM, (2008)
B. Gold, A. Ailamaki, L. Huston, and B. Falsafi. DaMoN '05: Proceedings of the 1st international workshop on Data management on new hardware, page 1. New York, NY, USA, ACM, (2005)
C. Cranor, T. Johnson, O. Spataschek, and V. Shkapenyuk. SIGMOD '03: Proceedings of the 2003 ACM SIGMOD international conference on Management of data, page 647--651. New York, NY, USA, ACM, (2003)
N. Bandi, A. Metwally, D. Agrawal, and A. Abbadi. SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, page 247--256. New York, NY, USA, ACM, (2007)
D. Agrawal, and A. Abbadi. DaMoN '05: Proceedings of the 1st international workshop on Data management on new hardware, page 1. New York, NY, USA, ACM, (2005)