Abstract：Personal Web Libraryorganizing and visualizing Web browsing history Purpose Modern Web browsers all provide a history function that allows users to see a list of URLs they have visited in chronological orderThe history log contains rich information but is seldom used because of the tedious nature of scrolling through long listsThis paper aims to propose a new way to improve usersWeb browsing experience by analyzingclustering and visualizing their browsing historyDesignmethodologyapproach The authors developed a system called Personal Web Library to help users develop awareness of and understand their Web browsing patternsidentify their topics of interest and retrieve previously visited Web pages more easilyFindings User testing showed that this system is usable and attractiveIt found that users can easily see patterns and trends at different time granularitiesrecall pages from the past and understand the local context of a browsing sessionIts flexibility provides users with much more information than the traditional history function in modern Web browsersParticipants in the study gained an improved awareness of their Web browsing patternsParticipants mentioned that they were willing to improve their time management after viewing their browsing patternsPractical implications As more and more daily activities rely on the internet and Web browsersbrowsing data captures a large part of userslivesProviding users with interactive visualizations of their browsing history can facilitate personal information managementtime management and other meta-level activitiesOriginalityvalue This paper aims to help users gain insights into and improve their Web browsing experiencethe authors hope that the work they conducted can spur more research contributions in this underdeveloped yet important areaThis article focuses on the browsing history of analysisclassificationand visualization users to improve its web browsing experienceAmong themdata exploration technology can be applied to identify and extract useful information and patterns from a large amount of browsing data