Title
Enhanced Web Page Content Visualization with Firefox
Abstract
This paper aims at presenting how natural language processing and machine learning techniques can help the internet surfer to get a better overview of the pages he is reading. The proposed demo is a Firefox extension which can show a semantic graph of the text in the page that is currently loaded in the browser. The user can also get a summary of the web page she is looking at by choosing to display only the more important nodes in the semantic graph representation of the document, where importance of the nodes is obtained by machine learning techniques.
Year
DOI
Venue
2009
10.1007/978-3-642-04174-7_48
ECML/PKDD
Keywords
Field
DocType
important node,enhanced web page content,web page,firefox extension,natural language processing,better overview,semantic graph,internet surfer,proposed demo,semantic graph representation,graph representation,machine learning,web pages
Static web page,Graph,World Wide Web,Information retrieval,Web page,Visualization,Computer science,WYCIWYG,Graph (abstract data type),The Internet
Conference
Volume
ISSN
Citations 
5782
0302-9743
2
PageRank 
References 
Authors
0.38
2
3
Name
Order
Citations
PageRank
lorand dali1233.85
Delia Rusu2405.61
Dunja Mladenic31484170.14