Abstract
The tremendous growth in the number of files stored in filesystems makes it increasingly difficult to find desired files. Traditional keyword-based search engines are incapable of retrieving files that do not include keywords. To tackle this problem, we use file-access logs to derive intertask relationships for file search. Our observations are that 1) files related to the same task are frequently used together, and 2) a set of Rename, Move, and Copy (RMC) operations tends to initiate a new task. We have implemented a system named SUGOI, which detects two types of task, FI tasks and RMC tasks, from file-access logs. An FI task corresponds to a group of files frequently accessed together. An RMC task is generated by RMC operations and then constructs a graph of intertask relationships based on the influence of RMC operations and the similarity between tasks. In utilizing detected tasks and intertask relationships, our system expands the search results of a keyword-based search engine. Experiments using actual file-access logs indicate that the proposed approach significantly improves search results.
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Wu, Y., Otagiri, K., Watanabe, Y., Yokota, H. (2011). A File Search Method Based on Intertask Relationships Derived from Access Frequency and RMC Operations on Files. In: Hameurlain, A., Liddle, S.W., Schewe, KD., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2011. Lecture Notes in Computer Science, vol 6860. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23088-2_27
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DOI: https://doi.org/10.1007/978-3-642-23088-2_27
Publisher Name: Springer, Berlin, Heidelberg
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