This paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks.
Telling Stories Fast / M. Borassi;P. Crescenzi;V. Lacroix;A. Marino;M.-F. Sagot;P. Vieira Milreu. - STAMPA. - 7933:(2013), pp. 200-211. (Intervento presentato al convegno 12th International Symposium on Experimental Algorithms) [10.1007/978-3-642-38527-8_19].
Telling Stories Fast
CRESCENZI, PIERLUIGI;MARINO, ANDREA;
2013
Abstract
This paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.