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Semantic Identification: Balancing between Complexity and Validity


An efficient scheme for identifying semantic entities within data sets such as multimedia documents, scenes, signals, and so forth, is proposed in this work. Expression of semantic entities in terms of syntactic properties is modelled with appropriately defined finite automata, which also model the identification procedure. Based on the structure and properties of these automata, formal definitions of attained validity and certainty and also required complexity are defined as metrics of identification efficiency. The main contribution of the paper relies on organizing the identification and search procedure in a way that maximizes its validity for bounded complexity budgets and reversely minimizes computational complexity for a given required validity threshold. The associated optimization problem is solved by using dynamic programming. Finally, a set of experiments provides insight to the introduced theoretical framework.


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Correspondence to M. Falelakis.

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Falelakis, M., Diou, C. & Delopoulos, A. Semantic Identification: Balancing between Complexity and Validity. EURASIP J. Adv. Signal Process. 2006, 041716 (2006).

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  • Information Technology
  • Computational Complexity
  • Dynamic Programming
  • Quantum Information
  • Identification Procedure