Detection of child exploiting chatsfrom a mixed chat dataset as a text classification task

Title: Detection of child exploiting chatsfrom a mixed chat dataset as a text classification task
Creator: Yearwood, John; Miah, Md Waliur Rahman; Kulkarni, Siddhivinayak
Date: 2011
Type: Text; Conference paper
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/34325
Identifier: vital:5207
Abstract: There is a rapidly growing body of work in the use of Embodied Conversational Agents (ECA) to convey complex contextual relationships through verbal and non-verbal communication, in domains ranging from military C2 to e-learning. In these applications the subject matter expert in often naive to the technical requirements of ECAs. ENGAGE (the Extensible Natural Gesture Animation Generation Engine) is desgined to automatically generate appropriate and 'realistic' animation for ECAs based on the content provided to them. It employs syntactic analysis of the surface text and uses predefined behaviours for the ECA. We discuss the design of this system, its current applications and plans for its future development.
Publisher: Canberra, Australia Australasian Language Technology Association
Relation: Proceedings of Australasian Language Technology Association Workshop
Rights: Copyright unknown
Rights: This metadata is freely available under a CCO license
Reviewed

		Thumbnail	File	Description	Size	Format