Optimal query complexity bounds for finding graphs

We consider the problem of finding an unknown graph by using two types of queries with an additive property. Given a graph, an additive query asks the number of edges in a set of vertices while a cross-additive query asks the number of edges crossing between two disjoint sets of vertices. The queries ask sum of weights for the weighted graphs. These types of queries were partially motivated in DNA shotgun sequencing and linkage discovery problem of artificial intelligence. For a given unknown weighted graph G with n vertices, m edges, and a certain mild condition on weights, we prove that there exists a non-adaptive algorithm to find the edges of G using O " m log n log m " queries of both types provided that m n for any constant > 0. For an unweighted graph, it is shown that the same bound holds for all range of m. This settles a conjecture of Grebinski [23] for finding an unweighted graph using additive queries. We also consider the problem of finding the Fourier coef...

• Type: Journal
• Year: 2010
• Where: AI
• Authors: Sung-Soon Choi, Jeong Han Kim
• Keywords: AI 2010, Artificial Intelligence, Unknown Weighted Graph, Unweighted Graph, Weighted Graph