Publication detail

Measuring Web Page Similarity Based on Textual and Visual Properties

BARTÍK, V.

Original Title

Measuring Web Page Similarity Based on Textual and Visual Properties

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

BARTÍK, V.

RIV year

2012

Released

3. 5. 2012

Publisher

Springer Verlag

Location

Zakopane

ISBN

978-3-642-29349-8

Book

The 11th International Conference on Artificial Intelligence and Soft Computing

Edition

Lecture Notes in Artificial Intelligence, Vol. 7268

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Number

7268

State

Federal Republic of Germany

Pages from

13

Pages to

21

Pages count

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/"
}

Documents

icaisc.pdf