Biological-inspired algorithms for dynamic search in web graphs

Abstract

We propose a biological-inspired algorithmic procedure for improving the precision level in respect to a web user's query. This algorithm is capable of tracing relevant information in web graphs, imitating the mission of foraging ants. Our proposal is an Ant Colony Optimization (ACO) modification, however its differentiation lies in the fact that no predefined graph is employed, since the search graph is dynamically constructed during the algorithm execution. Despite some weaknesses in terms of time execution, it was evaluated that the effectiveness of the algorithm was quite satisfying in large web graph sets. © 2011 IEEE.