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.
Cite
Text
Dali et al. "Enhanced Web Page Content Visualization with Firefox." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009. doi:10.1007/978-3-642-04174-7_48Markdown
[Dali et al. "Enhanced Web Page Content Visualization with Firefox." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009.](https://mlanthology.org/ecmlpkdd/2009/dali2009ecmlpkdd-enhanced/) doi:10.1007/978-3-642-04174-7_48BibTeX
@inproceedings{dali2009ecmlpkdd-enhanced,
title = {{Enhanced Web Page Content Visualization with Firefox}},
author = {Dali, Lorand and Rusu, Delia and Mladenic, Dunja},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2009},
pages = {718-721},
doi = {10.1007/978-3-642-04174-7_48},
url = {https://mlanthology.org/ecmlpkdd/2009/dali2009ecmlpkdd-enhanced/}
}