以情境感知內容調適提升網際普遍存取能力; Increasing Pervasive Web Accessibility with Context Aware Content Adaptation

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Network Learning Technology > Electronic Thesis & Dissertation > Item 987654321/10136

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/10136

Title:	以情境感知內容調適提升網際普遍存取能力;Increasing Pervasive Web Accessibility with Context Aware Content Adaptation
Authors:	吳建德;Jian-De Wu
Contributors:	網路學習科技研究所
Keywords:	普遍存取;內容調適;情境感知;universal access;content adaptation;context aware
Date:	2005-06-24
Issue Date:	2009-09-22 12:07:28 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	由於資訊科技快速的成長，在網路上可以發現各式各樣且不同性質的多媒體內容(multimedia content)。雖然很多行動裝置均已經支援網際網路的應用，能夠擷取網際網路上面的資訊，但是由於網際網路的興起遠比現今行動裝置來的早，因此大多數的資料的呈現方式並未符合目前的行動裝置性能，使得使用者在觀看內容時產生視覺上的不便，而且多媒體內容種類五花八門，諸如文字、圖片、語音與影片等等，並不是所有種類的內容都適合在使用者手中的裝置呈現，例如，個人數位助理(PDA)或手機，螢幕較小，運算能力差，網路連線能力較弱，所以勢必有些內容不適合或不能在這樣的裝置上呈現。我們提出一個具備動態考量使用者的情境調適機制(CCAF)，能夠使現今裝置能夠經由內容調適技術將取得的多媒體內容予以最佳化的呈現。 In pervasive computing environment, user will use pervasive device to access web content. Currently, using pervasive device access most of web contents presents bad visualized effect, which impeded knowledge sharing. In addition, the great diversity of user's preference, environment, and device increases the difficulty and complexity of content design. Therefore, we proposed a context-based adaptation solution, named Context Oriented Content Adaptation Framework (CCAF), that helping user to overcome accessing problems. The proposed framework is started from multimedia content decomposition. Each object is adapted according to specified adaptation rule, which determined from the user’s context. The template composition dynamically produces the corresponding style-sheet. Then an adapted XML-content will show on user’s device. Experiments show that CCAF is an extensible and scalable middleware system providing content adaptation service among heterogeneous context.
Appears in Collections:	[Graduate Institute of Network Learning Technology] Electronic Thesis & Dissertation

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