Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
How people revisit web pages: empirical findings and implications for the design of history systems
International Journal of Human-Computer Studies - Special issue: World Wide Web usability
An Empirical Analysis of Web Page Revisitation
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 5 - Volume 5
iDM: a unified and versatile data model for personal dataspace management
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
iTrails: pay-as-you-go information integration in dataspaces
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Multi-dimensional search for personal information management systems
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Analyzing user behavior to rank desktop items
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Information re-finding by context: a brain memory inspired approach
Proceedings of the 20th ACM international conference on Information and knowledge management
Design and implementation of a context-based media retrieval system
CVM'12 Proceedings of the First international conference on Computational Visual Media
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Many users need to refer to content in existing files (pictures, tables, emails, web pages and etc.) when they write documents(programs, presentations, proposals and etc.), and often need to revisit these referenced files for review, revision or reconfirmation. Therefore it is meaningful to discover an approach to help users revisit these references effectively. Traditional approaches (file explorer, desktop search, and etc.) fail to work in this case. In this paper, we propose an efficient solution for this problem. We firstly define a new personal data relationship: Context-based Reference (CR), which is generated by user behaviors. We also propose efficient methods to identify CR relationship and present a new type of query based on it: Context-based Query(C-Query), which helps users efficiently revisit personal documents based on CR relationship. Our experiments validate the effectiveness and efficiency of our methods.