Abstract
AbstractAn ad hoc data source is any semi-structured, non-standard data source. The format of such data sources is often evolving and frequently lacking documentation. Consequently, off-the-shelf tools for processing such data often do not exist, forcing analysts to develop their own tools, a costly and time-consuming process. In this paper, we present an incremental algorithm that automatically infers the format of large-scale data sources. From the resulting format descriptions, we can generate a suite of data processing tools automatically. The system can handle large-scale or streaming data sources whose formats evolve over time. Furthermore, it allows analysts to modify inferred descriptions as desired and incorporates those changes in future revisions.KeywordsEdit DistanceInitial DescriptionDependent PairMembership QueryGrammatical InferenceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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