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USENIX, The Advanced Computing Systems Association

2007 USENIX Annual Technical Conference

Pp. 171–184 of the Proceedings

Using Provenance to Aid in Personal File Search

Sam Shah, University of Michigan; Craig A.N. Soules, HP Labs; Gregory R. Ganger, Carnegie Mellon University; Brian D. Noble, University of Michigan


As the scope of personal data grows, it becomes increasingly difficult to find what we need when we need it. Desktop search tools provide a potential answer, but most existing tools are incomplete solutions: they index content, but fail to capture dynamic relationships from the user’s context. One emerging solution to this is context-enhanced search, a technique that reorders and extends the results of content-only search using contextual information. Within this framework, we propose using strict causality, rather than temporal locality, the current state of the art, to direct contextual searches. Causality more accurately identities data flow between files, reducing the false-positives created by context-switching and background noise. Further, unlike previous work, we conduct an online user study with a fully-functioning implementation to evaluate user-perceived search quality directly. Search results generated by our causality mechanism are rated a statistically-signi cant 17% higher on average over all queries than by using content-only search or context-enhanced search with temporal locality.
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Last changed: 29 August 2007 ac