Accession Number : AD1023352


Title :   Efficient Algorithmic Frameworks via Structural Graph Theory


Descriptive Note : Technical Report,01 Aug 2012,30 Sep 2016


Corporate Author : Massachusetts Institute of Technology Cambridge United States


Personal Author(s) : Demaine,Erik D ; Hajiaghayi,Mohammad T


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1023352.pdf


Report Date : 28 Oct 2016


Pagination or Media Count : 21


Abstract : In this project, we developed many new efficient algorithms for analysis of networks. We have published over 100 papers during the course of this project, and we launched a new website BigDND [http://projects.csail.mit.edu/dnd/] for distributing large network data and tools for analyzing them. Within network science, our research develops algorithms to enable efficient and guaranteed-quality analysis of abroad range of types of networks, from social networks to computer networks and transportation networks. Real-world social networks of interest include online services (Facebook, Google , Twitter), coauthorship/collaboration among people (arXiv, DBLP, patents), phone calls (AT\ and T, NSA), in-person interactions (FBI, Pentagon), geographic hierarchical neighborhoods (living or working together, on the same block, in the same district or city), and shared interests (Netflix, Amazon, Match.com).


Descriptors :   computer networks , graph theory , zerosum games , social networking services , game theory , network topology , flow network , digital data , energy consumption , polynomials


Subject Categories : Theoretical Mathematics


Distribution Statement : APPROVED FOR PUBLIC RELEASE