Title :
Identifying the Most Connected Vertices in Hidden Bipartite Graphs Using Group Testing
Author :
Jianguo Wang ; Lo, Eric ; Yiu, Man Lung
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
Abstract :
A graph is called hidden if the edges are not explicitly given and edge probe tests are required to detect the presence of edges. This paper studies the k most connected vertices (kMCV) problem on hidden bipartite graphs, which has applications in spatial databases, graph databases, and bioinformatics. There is a prior work on the kMCV problem, which is based on the “2-vertex testing” model, i.e., an edge probe test can only reveal the existence of an edge between two individual vertices. We study the kMCV problem, in the context of a more general edge probe test model called “group testing.” A group test can reveal whether there exists some edge between a vertex and a group of vertices. If group testing is used properly, a single invocation of a group test can reveal as much information as multiple invocations of 2-vertex tests. We discuss the cases and applications where group testing could be used, and present an algorithm, namely, GMCV, that adaptively leverages group testing to solve the kMCV problem.
Keywords :
graph theory; 2-vertex testing model; GMCV; bioinformatics; connected vertices; edge probe tests; graph databases; group testing; hidden bipartite graphs; k most connected vertices problem; kMCV problem; spatial databases; Bioinformatics; Bipartite graph; Image edge detection; Probes; Proteins; Switches; Testing; Bioinformatics; Bipartite graph; Image edge detection; Probes; Proteins; Query processing; Switches; Testing; graphs and networks;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2012.178