Automatic page scrolling for mobile Web search

Abstract

Nowadays the usage of mobile phones is widely spread in our daily life. We use mobile phones as a camera, radio, music player, and even an internet browser. As most Web pages were originally designed for desktop computers with large screens, viewing them on smaller displays involves a number of horizontal and vertical page scrolling. To save mobile Web search fatigue caused by repeated scrolling, we investigate the automatic Web page scrolling problem based on two observations. First, every web page has many different parts that do not have the equal importance to an end user, and the user is often interested in a certain part of the Web page. Second, the ease of use of text-entry in mobile phones compare to the desktop computers', users usually prefer to search the Web just once and get the needed answer. Compared to the existing efforts on page layout modification and content splitting for easy page navigation on mobile displays, we present a simple yet effective approach of automatic page scrolling for mobile Web search, while keeping the original Web page content keeps its integrity and hence, preventing any loss of information. We work with the Document Object Model (DOM) of the clicked page by user, compute the relevance of each paragraph of the Web page based on the tf*idf (term frequency*inverse document frequency) values of user's search keywords occurring in that paragraph. The focus of the browser will be automatically scrolled to the most relevant one. Our user study shows that the proposed approach can achieve 96.47% scrolling accuracy under one search keyword, and 94.78% under multiple search keywords, while the time spending in computing the most important part does not vary much from the number of search keywords. The users can save up to 1.5 sec in searching and finding the needed information compare to the best case of our user study.