With the rapid development of wireless communication technology, in addition to desktop computers, many users are accessing the internet from hand-held appliances, such as tablets, PDAs, and cellular phones. Many new computation paradigms, such as pervasive computing and ubiquitous computing, have been proposed to embrace this emerging portable computation framework. However, because of the difference in users’ speed in adopting new technologies, hand-held devices in use have miscellaneous hardware limitations, such as CPU speed, power, memory, bandwidth, and image resolutions. They also have various restrictions in software support, such as operating system, installed programs, real-time processing capability, and rendering functionality. These ad hoc limitations have become barriers in human-computer interaction. Most web contents, such as web pages and images, are mainly in the HTML format, which is designed for desktop computers. Without proper modification, most rendered web contents in hand-held devices encounter distorted or fragmented user interface, broken images, slow responses, etc. These ad hoc characteristics of hand-held devices have become a barrier in enhancing web availability. In this chapter, we illustrate how a semantics-based content adaptation framework could be utilized to fill up the computational gap between mobile devices and desktop computers. The transcoding mechanism of our framework, called Content Adaptation Proxy Server [CAPS], resides behind web servers. In CAPS, web pages and image files are transcoded according to: (1) RDF (Resource Description Framework) (Manola et al., 2004) of web content; and (2) semantics extracted from the CC/PP (Composite Capability Preferences Profiles) (Klyne et al., 2004) client device configuration. These semantic properties will be stored and interpreted inside the Jena Inference System (Carroll et al., 2004) as knowledge facts to obtain proper transcoding parameters for each particular device. Then web pages with proper layout modification and images with proper rendering parameters for each particular device will be constructed and delivered. This technology will recreate contents suitable for resource-limited devices to balance information loss and information availability. For the rest of this chapter, we will review related work in Section 2. In Section 3, we describe the design principle and system architecture of CAPS. Semantics extraction and knowledge base construction for the Jena Inference System are discussed in Sections 4 and 5.
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