World-Wide Web consists of a huge number of unstruc- tured hypertext documents, but it also contains structured data in the form of HTML tables. Many of these tables contain both relational-style data and a small "schema" of labeled and typed columns, making each such table a small structured database. The WebTables project is an effort to extract and make use of the huge number of these structured tables on the Web. A clean collection of relational-style ta- bles could be useful for improving web search, schema de- sign, and many other applications. This paper describes the first stage of the WebTables project. First, we give an in-depth study of the Web's HTML table corpus. For example, we extracted 14.1 billion HTML ta- bles from a several-billion-page portion of Google's general- purpose web crawl, and estimate that 154 million of these tables contain high-quality relational-style data. We also de- scribe the crawl's distribution of table sizes and data types. Second, we describe a system for performing relation recov- ery. The Web mixes relational and non-relational tables indiscriminately (often on the same page), so there is no simple way to distinguish the 1.1% of good relations from the remainder, nor to recover column label and type infor- mation. Our mix of hand-written detectors and statistical classifiers takes a raw Web crawl as input, and generates a collection of databases that is five orders of magnitude larger than any other collection we are aware of. Relation recovery achieves precision and recall that are comparable to other domain-independent information extraction systems.
['Michael J. Cafarella', 'Alon Y. Halevy', 'Yang Zhang', 'Daisy Zhe Wang', 'Eugene Wu']
Uncovering the Relational Web