Minimizing Uncertainty in Semantic Identification When Computing Resources Are Limited

Manolis Falelakis, Christos Diou, Manolis Wallace, Anastasios Delopoulos

Abstract: In this paper we examine the problem of automatic semantic identification of entities in multimedia documents from a computing point of view. Specifically, we identify as main points to consider the storage of the required knowledge and the computational complexity of the handling of the knowledge as well as of the actual identification process. In order to tackle the above we utilize (i) a sparse representation model for storage, (ii) a novel transitive closure algorithm for handling and (iii) a novel approach to identification that allows for the specification of computational boundaries.