Linked Life Data

20566337

Source:http://linkedlifedata.com/resource/pubmed/id/20566337

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2010-8-23
pubmed:abstractText
From ancient times to the present day, social networks have played an important role in the formation of various organizations for a range of social behaviors. As such, social networks inherently describe the complicated relationships between elements around the world. Based on mathematical graph theory, social network analysis (SNA) has been developed in and applied to various fields such as Web 2.0 for Web applications and product developments in industries, etc. However, some definitions of SNA, such as finding a clique, N-clique, N-clan, N-club and K-plex, are NP-complete problems, which are not easily solved via traditional computer architecture. These challenges have restricted the uses of SNA. This paper provides DNA-computing-based approaches with inherently high information density and massive parallelism. Using these approaches, we aim to solve the three primary problems of social networks: N-clique, N-clan, and N-club. Their accuracy and feasible time complexities discussed in the paper will demonstrate that DNA computing can be used to facilitate the development of SNA.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1872-8324
pubmed:author
pubmed:copyrightInfo
Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
101
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
222-32
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Applying DNA computation to intractable problems in social network analysis.
pubmed:affiliation
Department of Computer Science & Information Engineering, National Central University, Taiwan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't