Enhancing the precision of content analysis in content adaptation using entropy-based fuzzy reasoning

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51541

Title:	Enhancing the precision of content analysis in content adaptation using entropy-based fuzzy reasoning
Authors:	Chen,RCS;Yang,SJH;Zhang,J
Contributors:	資訊工程學系
Keywords:	AWARE WEB SERVICES;SYSTEM;DESIGN
Date:	2010
Issue Date:	2012-03-27 18:55:38 (UTC+8)
Publisher:	國立中央大學
Abstract:	Content adaptation is a well-known technique to help portable devices present Web pages as smoothly as desktops do. Because of limited I/O and weak transmission capability, adaptations are usually performed by either transcoding or resizing multimedia components. In this paper, we propose a novel semantic coherence-retained content adaptation approach, namely functionality sense-based content adaptation (FSCA). Our goal is to avoid semantic distortions when rearranging a Web page on different screen sizes. Simulating entropy-based fuzzy reasoning in human cognition, we introduce Relevance of Functionality (RoF) to quantitatively represent the similarity intensity between two presentation objects (groups) based on their functionalities. We present an algorithm of calculating RoF and a procedure that uses RoF to decide content adaptation degree. Our experiments verify the feasibility and effectiveness of FSCA. (c) 2010 Elsevier Ltd. All rights reserved.
Relation:	EXPERT SYSTEMS WITH APPLICATIONS
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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