Detail publikace

Measuring Web Page Similarity Based on Textual and Visual Properties

BARTÍK, V.

Originální název

Measuring Web Page Similarity Based on Textual and Visual Properties

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Measuring web page similarity is a very important task in the area of web mining and information retrieval. This paper introduces the method for measuring web page similarity, which considers both textual and visual properties of pages. Textual properties of a page are described by means of modified weight vector space model. General visual properties are captured via segmentation of a page, which divides a page into visual blocks, properties of which are stored into a vector of visual properties. These both vectors are then used to compute the whole web page similarity. This method will be described in detail and results of several experiments are also introduced in this paper.

Klíčová slova

Web page similarity, clustering, vector space model, vector distance, term weighting, visual blocks.

Autoři

BARTÍK, V.

Rok RIV

2012

Vydáno

3. 5. 2012

Nakladatel

Springer Verlag

Místo

Zakopane

ISBN

978-3-642-29349-8

Kniha

The 11th International Conference on Artificial Intelligence and Soft Computing

Edice

Lecture Notes in Artificial Intelligence, Vol. 7268

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Číslo

7268

Stát

Spolková republika Německo

Strany od

13

Strany do

21

Strany počet

9

URL

https://www.fit.vut.cz/research/publication/9850/

BibTex

@inproceedings{BUT76500,
  author="Vladimír {Bartík}",
  title="Measuring Web Page Similarity Based on Textual and Visual Properties",
  booktitle="The 11th International Conference on Artificial Intelligence and Soft Computing",
  year="2012",
  series="Lecture Notes in Artificial Intelligence, Vol. 7268",
  journal="Lecture Notes in Computer Science",
  number="7268",
  pages="13--21",
  publisher="Springer Verlag",
  address="Zakopane",
  isbn="978-3-642-29349-8",
  issn="0302-9743",
  url="https://www.fit.vut.cz/research/publication/9850/"
}

Dokumenty

icaisc.pdf