Automatic Web Page Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F08%3A00042213" target="_blank" >RIV/00216224:14330/08:00042213 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Automatic Web Page Classification
Original language description
Aim of this paper is to describe a method of automatic web page classification to semantic domains and its evaluation. The classification method exploits machine learning algorithms and several morphological as well as semantical text processing tools. In contrast to general text document classification, in the web document classification, there are often problems with short web pages. In this paper we proposed two approaches to eliminate the lack of information. In the first one we consider a wider context of a web page. That means we analyze web pages referenced from the investigated page. The second approach is based on sophisticated term clustering by their similar grammatical context. This is done using statistic corpora tool the Sketch Engine.
Czech name
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Czech description
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Project
<a href="/en/project/LC536" target="_blank" >LC536: Integrated center for natural language processing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Recent Advances in Slavonic Natural Language Processing
ISBN
978-80-210-4741-9
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
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Publisher name
Faculty of Informatics, Masaryk University
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2008
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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