2012年5月30日水曜日

Visualization for Large-scale Traffic Simulation

http://www.trsp.net/cow/video_trafficmixer.html

Visualizing the Kyoto road network by Prof.Hattori
http://www.youtube.com/watch?v=qYJLVZvvKR4&feature=relmfu
http://www.youtube.com/watch?v=I2vvIA9sKRo

Google Earth + KML による視覚化。いまいち。
http://www.youtube.com/watch?v=FEMOpMtenvE
http://www.youtube.com/watch?NR=1&feature=endscreen&v=bkR2ZcLHufI

Visualization with Google Earth
http://www.gtrek.co.uk/GTrek-Flight.kmz

2012年5月14日月曜日

IPDPS 2012 におけるグラフ処理に関する論文

Regular Track に8本もグラフに関する論文が採択されているところを見ると、大規模グラフに関する研究が近年ますます盛んになっている証拠である。http://www.ipdps.org/ipdps2012/2012_advance_program.html


Fast and Efficient Graph Traversal Algorithm for CPUs : Maximizing Single-Node Efficiency
Jatin Chhugani (Intel Corporation, USA); Nadathur Satish (Intel Corporation, USA); Changkyu Kim (Intel Corporation, USA); Jason Sewall (Intel Corporation, USA); Pradeep Dubey (Intel Corporation, USA)
SAHAD: Subgraph Analysis in Massive Networks Using Hadoop
Zhao Zhao (Virginia Tech, USA); Guanying Wang (Virginia Tech, USA); Ali R Butt (Virginia Tech., USA); Maleq Khan (Virginia Tech, USA); Vullikanti S Anil Kumar (Virginia Tech, USA); Madhav Marathe (Virginia Tech, USA)
Accelerating nearest neighbor search on manycore systems
Lawrence Cayton (Max Planck Institute for Intelligent Systems, Germany)
Optimizing large-scale graph analysis on multithreaded, multicore platforms
Guojing Cong (IBM T.J. Watson Research Center, USA)

Multi-core spanning tree algorithms using the disjoint-set data structure
Fredrik Manne (University of Bergen, Norway); Md. Mostofa Ali Patwary (Northwestern University, USA); Peder Refsnes (University of Bergen, Norway)
Graph Partitioning for Reconfigurable Topology
Deepak Ajwani (University College Cork, Ireland); Shoukat Ali (Dublin Research Lab, IBM, USA); John P. Morrison (University Cork, Ireland)
Multithreaded Clustering for Multi-level Hypergraph Partitioning
Umit V. Catalyurek (The Ohio State University, USA); Mehmet Deveci (The Ohio State University, USA); Kamer Kaya (The Ohio State University, USA); Bora Ucar (CNRS, France)              
Multithreaded Algorithms for Maximum Matching in Bipartite Graphs
Ariful Azad (Purdue University, USA); Mahantesh Halappanavar (Pacific Northwest National Laboratory, USA); Sivasankaran Rajamanickam (Sandia National Laboratories, USA); Erik G. Boman (Sandia National Laboratories, USA); Arif Khan (Purdue University, USA); Alex Pothen (Purdue University, USA)

2012年5月10日木曜日

情報拡散に関する研究

Information Transfer in Social Media, WWW 2012
Greg Ver Steeg, Aram Galstyan

The Role of Social Networks in Information Diffusion, WWW 2012
Eytan Bakshy, Itamar Rosenn, Cameron Marlow, Lada Adamic

Recommendations to Boost Content Spread in Social Networks, WWW 2012
Vineet Chaoji, Sayan Ranu, Rajeev Rastogi, Rushi Bhatt


Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contagion on Twitter, WWW 2011
http://www.cs.cornell.edu/home/kleinber/www11-hashtags.pdf

Limiting the Spread of Misinformation in Social Networks, WWW 2011 
Ceren Budak, Divyakant Agrawal and Amr El Abbadi

Information Credibility on Twitter, WWW, 2011 
Carlos Castillo, Marcelo Mendoza and Bárbara Poblete

Information Spreading in Contex, WWW 2011

Information diffusion in online social networks

Survey Survey on Information Diffusion, 2008

Modeling Information Diffusion in Implicit Networks

Information Diffusion Through Blogspace, WWW2004
http://people.csail.mit.edu/dln/papers/blogs/idib.pdf
We study the dynamics of information propagation in environments of low-overhead personal publishing, using a large collection of weblogs over time as our example domain. We characterize and model this collection at two levels. First, we present a macroscopic characterization of topic propagation through our corpus, formalizing the notion of long-running “chatter” topics consisting recursively of “spike” topics generated by outside world events, or more rarely, by resonances within the community. Second, we present a microscopic characterization of propagation from individual to individual, drawing on the theory of infectious diseases to model
the flow. We propose, validate, and employ an algorithm to induce the underlying propagation network from a sequence of posts, and report on the results.