Harvesting relational tables from lists on the web

A large number of web pages contain data structured in the form of “lists”. Many such lists can be further split into multi-column tables, which can then be used in more semantically meaningful tasks. However, harvesting relational tables from such lists can be a challenging task. The lists are manually generated and hence need not have well defined templates – they have inconsistent delimiters (if any) and often have missing information. We propose a novel technique for extracting tables from lists. The technique is domain-independent and operates in a fully unsupervised manner. We first use multiple sources of information to split individual lines into multiple fields, and then compare the splits across multiple lines to identify and fix incorrect splits and bad alignments. In particular, we exploit a corpus of HTML tables, also extracted from the Web, to identify likely fields and good alignments. For each extracted table, we compute an extraction score that reflects ou...

• Type: Journal
• Year: 2011
• Where: VLDB
• Authors: Hazem Elmeleegy, Jayant Madhavan, Alon Y. Halevy
• Keywords: Database, Extracted Tables, Query-able Relational Tables, Relational Tables, VLDB 2011