Detail publikace

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

ZELENÝ, J. BURGET, R.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

ZELENÝ, J.; BURGET, R.

Rok RIV

2013

Vydáno

12. 6. 2013

Nakladatel

Association for Computing Machinery

Místo

Madrid

ISBN

978-1-4503-1850-1

Kniha

The Third International Conference on Web Intelligence, Mining and Semantics

Strany od

1

Strany do

12

Strany počet

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/"
}