Icon-Based Communication: A Method for Interpreting Sequences of Conceptual Symbols

Title: Icon-Based Communication: A Method for Interpreting Sequences of Conceptual Symbols

Abstract: This research explores a method for interpreting sequences of conceptual symbols, such as icons, to convey complex meanings. The approach is based on an electronic dictionary containing semantic information, which allows for the construction of conceptual graphs representing meaning and facilitating natural language sentence generation. This method addresses the challenge of expressing abstract relations between concepts without the use of linguistic communication.

Main Research Question: How can we develop a method to interpret sequences of conceptual symbols, such as icons, to convey complex meanings in a context where linguistic communication is limited or unavailable?

Methodology: The research proposes a method that involves assigning significance to a sequence of information items by building conceptual relations between them. This method is applied to a set of conceptual symbols, such as icons, to create a structured information pattern that reflects the complex meanings of the symbols.

Results: The research demonstrates that the proposed method can successfully interpret sequences of conceptual symbols to convey complex meanings. The results show that the method is effective in building knowledge networks from icons, as well as in representing conceptual inheritance and semantic associations.

Implications: The research has significant implications for the field of computer-assisted language learning. It provides a solution to the challenge of conveying complex meanings using only conceptual symbols, such as icons, without the use of linguistic communication. The method can be applied to develop software that aids in communication for individuals with speech impairments or those learning a second language. Additionally, the research contributes to the development of symbolic formulas in AI and linguistic theories that reflect human natural language and conceptual relations.

Link to Article: https://arxiv.org/abs/0109020v1 Authors: arXiv ID: 0109020v1