Interactive semantics

Research output: Contribution to journalArticle

View graph of relations Save citation

Open

Authors

Research units

Abstract

Much research pursues machine intelligence through better representation of semantics. What is semantics? People in different areas view semantics from different facets although it accompanies interaction through civilization. Some researchers believe that humans have some innate structure in mind for processing semantics. Then, what the structure is like? Some argue that humans evolve a structure for processing semantics through constant learning. Then, how the process is like? Humans have invented various symbol systems to represent semantics. Can semantics be accurately represented? Turing machines are good at processing symbols according to algorithms designed by humans, but they are limited in ability to process semantics and to do active interaction. Super computers and high-speed networks do not help solve this issue as they do not have any semantic worldview and cannot reflect themselves. Can future cyber-society have some semantic images that enable machines and individuals (humans and agents) to reflect themselves and interact with each other with knowing social situation through time? This paper concerns these issues in the context of studying an interactive semantics for the future cyber-society. It firstly distinguishes social semantics from natural semantics, and then explores the interactive semantics in the category of social semantics. Interactive semantics consists of an interactive system and its semantic image, which co-evolve and influence each other. The semantic worldview and interactive semantic base are proposed as the semantic basis of interaction. The process of building and explaining semantic image can be based on an evolving structure incorporating adaptive multi-dimensional classification space and self-organized semantic link network. A semantic lens is proposed to enhance the potential of the structure and help individuals build and retrieve semantic images from different facets, abstraction levels and scales through time.

Documents

  • Interactive semantics

    Rights statement: NOTICE: this is the author’s version of a work that was accepted for publication in Artificial intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Zhuge, H, 'Interactive semantics' Artificial intelligence, vol. 174, no. 2 (2010) DOI http://dx.doi.org/10.1016/j.artint.2009.11.014

    Accepted author manuscript, 322 KB, PDF-document

Details

Original languageEnglish
Pages (from-to)190-204
Number of pages15
JournalArtificial Intelligence
Volume174
Issue2
DOIs
StatePublished - Feb 2010

Bibliographic note

NOTICE: this is the author’s version of a work that was accepted for publication in Artificial intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Zhuge, H, 'Interactive semantics' Artificial intelligence, vol. 174, no. 2 (2010) DOI http://dx.doi.org/10.1016/j.artint.2009.11.014

    Keywords

  • semantics, interaction, classification, open systems, semantic link network, sSocial semantics, interactive semantics

DOI

Download statistics

No data available

Employable Graduates; Exploitable Research

Copy the text from this field...