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Publication detail
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
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
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/" }