Indexing for Interactive Exploration of Big Data Series

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Provided by: Association for Computing Machinery
Topic: Big Data
Format: PDF
Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available, which is not currently possible with the state-of-the-art indexing methods and for very large data series collections. In this paper, the authors present the first adaptive indexing mechanism, specifically tailored to solve the problem of indexing and querying very large data series collections. The main idea is that instead of building the complete index over the complete data set up-front and querying only later, they interactively and adaptively build parts of the index, only for the parts of the data on which the users pose queries.
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