Mobile content adaptation is a technology of effectively representing the contents originally built for the desktop PC on wireless mobile devices. Previous approaches for Web content adaptation are mostly device-dependent. Also, the content transformation to suit to a smaller device is done manually. As a result, the user has difficulty in selecting relevant information from a heavy volume of contents since the context information related to the content is not provided.

To resolve these problems, this paper proposes an enhanced method of Web content adaptation for mobile devices. In our system, the process of Web content adaptation consists of 4 stages including block filtering, block title extraction, block content summarization, and personalization through learning. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list.