Provenance is an increasingly important aspect of data management that is often underestimated and neglected by practitioners. In our work, we target the problem of reconstructing provenance of files in a shared folder setting, assuming that only standard filesystem metadata are available. We propose a content-based approach that is able to reconstruct provenance automatically, leveraging several similarity measures and edit distance algorithms, adapting and integrating them into a multi-signal pipeline. We discuss our research methodology and show some promising preliminary results. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Magliacane, S. (2012). Reconstructing provenance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7650 LNCS, pp. 399–406). Springer Verlag. https://doi.org/10.1007/978-3-642-35173-0_29
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