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Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Synthesizing Union Tables from the Web
BibTeX
@MISC{Ling_proceedingsof,
author = {Xiao Ling and Alon Halevy and Fei Wu and Cong Yu},
title = {Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Synthesizing Union Tables from the Web},
year = {}
}
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Abstract
Several recent works have focused on harvesting HTML tables from the Web and recovering their semantics [Cafarella et al., 2008a; Elmeleegy et al., 2009; Limaye et al., 2010; Venetis et al., 2011]. As a result, hundreds of millions of high quality structured data tables can now be explored by the users. In this paper, we argue that those efforts only scratch the surface of the true value of structured data on the Web, and study the challenging problem of synthesizing tables from the Web, i.e., producing never-before-seen tables from raw tables on the Web. Table synthesis offers an important semantic advantage: when a set of related tables are combined into a single union table, powerful mechanisms, such as temporal or geographical comparison and visualization, can be employed to understand and mine the underlying data holistically. We focus on one fundamental task of table synthesis, namely, table stitching. Within a given site, many tables with identical schemas can be scattered across many pages. The task of table stitching involves combining such tables into a single meaningful union table and identifying extra attributes and values for its rows so that rows from different original tables can be distinguished. Specifically, we first define the notion of stitchable tables and identify collections of tables that can be stitched. Second, we design an effective algorithm for extracting hidden attributes that are essential for the stitching process and for aligning values of those attributes across tables to synthesize new columns. We also assign meaningful names to these synthesized columns. Experiments on real world tables demonstrate the effectiveness of our approach. 1
Keyphrases
twenty-third international joint conference artificial intelligence synthesizing union table table synthesis raw table extra attribute many table never-before-seen table true value real world table geographical comparison effective algorithm many page underlying data table stitching meaningful name stitching process identical schema high quality single union table related table different original table important semantic advantage html table new column hidden attribute powerful mechanism data table stitchable table several recent work fundamental task single meaningful union table
