HistoryPaper: A Magazine-Style Layout of Representative Web Pages Extracted From Browsing History

Abstract

Web browsing history of people who use internet everyday represents processes they learned. Visualization of summarized browsing history can contribute to learn what we did. This paper proposes HistoryPaper, a system to extract representative Web pages from browsing history of users, and arranges them like a newspaper. The system helps users to remember what they did in a particular day. HistoryPaper firstly clusters browsed Web pages based on their contents. Then, it calculates the priority of Web pages from search terms and rality of accessed Web pages, and selects the representative page of each cluster. HistoryPaper arranges the representative pages by utilizing a layout algorithm following the magazine style applied in many news sites. This paper presents the numeric evaluation of the layout results to demonstrate the reasonableness of the algorithm.