document: Entity relation discovery from web tables and links The World-Wide Web consists not only of a huge number of unstructured texts , but also a vast amount of valuable structured data . Web tables ( 2 ) are a typical type of structured information that are pervasive on the web , and Web-scale methods that automatically extract web tables have been studied extensively ( 1 ) . Many powerful systems ( e.g. OCTOPUS ( 4 ) , Mesa ( 3 ) ) use extracted web tables as a fundamental component . In the database vernacular , a table is defined as a set of tuples which have the same attributes . Similarly , a web table is defined as a set of rows ( corresponding to database tuples ) which have the same column headers ( corresponding to database attributes ) . Therefore , to extract a web table is to extract a relation on the web . In databases , tables often contain foreign keys which refer to other tables . Therefore , it follows that hyperlinks inside a web table sometimes function as foreign keys to other relations whose tuples are contained in the hyperlink 's target pages . In this paper , we explore this idea by asking : can we discover new attributes for web tables by exploring hyperlinks inside web tables ? This poster proposes a solution that takes a web table as input . Frequent patterns are generated as new candidate relations by following hyperlinks in the web table . The confidence of candidates are evaluated , and trustworthy candidates are selected to become new attributes for the table . Finally , we show the usefulness of our method by performing experiments on a variety of web domains .
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