Affiliation:
1. ATR Center, Wright State University, Dayton, OH 45435, USA
Abstract
A better understanding of events many times requires the association and the efficient representation of multi-modal information. A good approach to this important issue is the development of a common platform for converting different modalities (such as images, text, etc.) into the same medium and associating them for efficient processing and understanding. In a previous paper we have presented a Local-Global graph model for the conversion of images into graphs with attributes and then into natural language (NL) text sentences [25]. Here, in this paper we propose the conversion of NL text sentences into graphs and then into Stochastic Petri-nets (SPN) descriptions in order to efficiently offer a model of associating "activities or changes" in multimodal information for events representation and understanding. The selection of the SPN graph model is due to its capability for efficiently representing structural and functional knowledge. Simple illustrative examples are provided for proving the concept proposed here.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software
Reference14 articles.
1. N. Chomsky, Syntactic Structures (Mouton, The Hague, 1957) p. 57.
2. J. Kanz and J. Fodor, The Structure in a Semantic Theory: The Structure of Language (Prentice Hall, 1964) pp. 479–518.
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