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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Falelakis, M., Diou, C., Wallace, M., & Delopoulos, A. (2005). Minimizing uncertainty in semantic identification when computing resources are limited. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 817–822). https://doi.org/10.1007/11550907_129
Mendeley helps you to discover research relevant for your work.