A TREE LEARNING APPROACH TO WEB DOCUMENT SECTIONAL HIERARCHY EXTRACTION

F. Canan Pembe, Tunga Güngör

2010

Abstract

There is an increasing availability of documents in electronic form due to the widespread use of the Internet. Hypertext Markup Language (HTML) which is mostly concerned with the presentation of documents is still the most commonly used format on the Web, despite the appearance of semantically richer markup languages such as XML. Effective processing of Web documents has several uses such as the display of content on small-screen devices and summarization. In this paper, we investigate the problem of identifying the sectional hierarchy of a given HTML document together with the headings in the document. We propose and evaluate a learning approach suitable to tree representation based on Support Vector Machines.

Paper Citation

in Harvard Style

Canan Pembe F. and Güngör T. (2010). A TREE LEARNING APPROACH TO WEB DOCUMENT SECTIONAL HIERARCHY EXTRACTION . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 447-450. DOI: 10.5220/0002590004470450

in Bibtex Style

@conference{icaart10,
author={F. Canan Pembe and Tunga Güngör},
title={A TREE LEARNING APPROACH TO WEB DOCUMENT SECTIONAL HIERARCHY EXTRACTION},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={447-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002590004470450},
isbn={978-989-674-021-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A TREE LEARNING APPROACH TO WEB DOCUMENT SECTIONAL HIERARCHY EXTRACTION
SN - 978-989-674-021-4
AU - Canan Pembe F.
AU - Güngör T.
PY - 2010
SP - 447
EP - 450
DO - 10.5220/0002590004470450