Minimizing uncertainty in semantic identification when computing resources are limited

Authors:
Manolis Falelakis;Christos Diou;Manolis Wallace;Anastasios Delopoulos
Affiliations:
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki - Greece;Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki - Greece;Department of Computer Science, University of Indianapolis, Athens Campus - Greece;Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki - Greece
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

Citing 5
Cited 0

Knowledge-Assisted Content-Based Retrieval for Multimedia Databases

IEEE MultiMedia
Semantic Modeling and Knowledge Representation in Multimedia Databases

IEEE Transactions on Knowledge and Data Engineering
Computationally efficient sup-t transitive closure for sparse fuzzy binary relations

Fuzzy Sets and Systems
Narrowing the semantic gap - improved text-based web document retrieval using visual features

IEEE Transactions on Multimedia
Factor graph framework for semantic video indexing

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

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.