Publication detail

Cluster-based Page Segmentation - a fast and precise method for web page pre-processing

ZELENÝ, J. BURGET, R.

Original Title

Cluster-based Page Segmentation - a fast and precise method for web page pre-processing

Type

conference paper

Language

English

Original Abstract

Segmenting a web page may be one of initial steps of information retrieval or content classification performed on that page. While there has been an extensive research in this area, the approaches usually focus either on performance or quality of the results. Vision based segmentation is one of the quality focused methods, which are considerably slow. This paper proposes an approach for boosting the performance of vision based algorithms. Our approach is based on concepts of modern web and a very common scenario in which an entire web site is processed at once. In this scenario, a great amount of performance boost can be gained by isomorphic mapping of previous results gathered from pages within the site to other pages on the same site. We provide the results of experiments performed on VIPS, the most common algorithm for page segmentation.

Keywords

VIPS, vision-based page segmentation, clustering, template,\\template detection

Authors

ZELENÝ, J.; BURGET, R.

RIV year

2013

Released

12. 6. 2013

Publisher

Association for Computing Machinery

Location

Madrid

ISBN

978-1-4503-1850-1

Book

The Third International Conference on Web Intelligence, Mining and Semantics

Pages from

1

Pages to

12

Pages count

12

URL

https://www.fit.vut.cz/research/publication/10252/

BibTex

@inproceedings{BUT106483,
  author="Jan {Zelený} and Radek {Burget}",
  title="Cluster-based Page Segmentation - a fast and precise method for web page pre-processing",
  booktitle="The Third International Conference on Web Intelligence, Mining and Semantics",
  year="2013",
  pages="1--12",
  publisher="Association for Computing Machinery",
  address="Madrid",
  doi="10.1145/2479787.2479792",
  isbn="978-1-4503-1850-1",
  url="https://www.fit.vut.cz/research/publication/10252/"
}