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|Abstract:||An 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.|
|Citation:||Zhu, Kenny Q., Kathleen Fisher, and David Walker. "LearnPADS + + : Incremental Inference of Ad Hoc Data Formats." In International Symposium on Practical Aspects of Declarative Languages, pp. 168-182. doi:10.1007/978-3-642-27694-1_13|
|Pages:||168 - 182|
|Type of Material:||Conference Article|
|Journal/Proceeding Title:||International Symposium on Practical Aspects of Declarative Languages|
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