0000000000349034
AUTHOR
Jeffery Westbrook
On finding common neighborhoods in massive graphs
AbstractWe consider the problem of finding pairs of vertices that share large common neighborhoods in massive graphs. We prove lower bounds on the resources needed to solve this problem on resource-bounded models of computation. In streaming models, in which algorithms can access the input only a constant number of times and only sequentially, we show that, even with randomization, any algorithm that determines if there exists any pair of vertices with a large common neighborhood must essentially store and process the input graph off line. In sampling models, in which algorithms can only query an oracle for the common neighborhoods of specified vertex pairs, we show that any algorithm must …
An Approximate Determinization Algorithm for Weighted Finite-State Automata
Nondeterministic weighted finite-state automata are a key abstraction in automatic speech recognition systems. The efficiency of automatic speech recognition depends directly on the sizes of these automata and the degree of nondeterminism present, so recent research has studied ways to determinize and minimize them, using analogues of classical automata determinization and minimization. Although, as we describe here, determinization can in the worst case cause poly-exponential blowup in the number of states of a weighted finite-state automaton, in practice it is remarkably successful. In extensive experiments in automatic speech recognition systems, deterministic weighted finite-state autom…