Unexpected results in automatic list extraction on the web

The discovery and extraction of general lists on the Web continues to be an important problem facing the Web mining community. There have been numerous studies that claim to automatically extract structured data (i.e. lists, record sets, tables, etc.) from the Web for various purposes. Our own recent experiences have shown that the list-finding methods used as part of these larger frameworks do not generalize well and therefore ought to be reevaluated. This paper briefly describes some of the current approaches, and tests them on various list-pages. Based on our findings, we conclude that analyzing a Web page's DOM-structure is not sufficient for the general list finding task.

• Type: Journal
• Year: 2010
• Where: SIGKDD
• Authors: Tim Weninger, Fabio Fumarola, Rick Barber, Jiawei Han, Donato Malerba
• Keywords: General List, Important Problem, Information Technology, SIGKDD 2010, Web Mining Community