Semantic Web Dog Food

Presented at: 20th International World Wide Web Conference (WWW2011)

by Tim Weninger, Fabio Fumarola, Cindy Xide Lin, Rick Barber, Jiawei Han, Donato Malerba

In this paper, we use the structural and relational information on the Web to find entity-pages. Specifically, given a Web site and an entity-page (e.g., department and faculty member homepage) we seek to find all of the entity-pages of the same type (e.g., all faculty members in the department). To do this, we propose a web structure mining method which grows parallel paths through the web graph and DOM trees. We show that by utilizing these parallel paths we can efficiently discover all entity-pages of the same type. Finally, we demonstrate the accuracy of our method with a case study on various domains.

Growing Parallel Paths for Entity-Page Discovery was presented at this event.

Keywords: World Wide Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2011/poster/growing-parallel-paths-for-entity-page-discovery

Explore this resource elsewhere:

• on Snorql
• on Sindice
• on dotAC Explorer