Podrobný výpis o publikaci

NAVRÁTIL, Jaromír a Lubomír POPELÍNSKÝ. Rapid prototyping of a web categorization tool. Online. In IDEAS '14 Proceedings of the 18th International Database Engineering & Applications Symposium. NY, USA: ACM New York, 2014, s. 294-297. ISBN 978-1-4503-2627-8. Dostupné z: https://dx.doi.org/10.1145/2628194.2628216.

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Základní údaje
Originální název	Rapid prototyping of a web categorization tool
Autoři	NAVRÁTIL, Jaromír (203 Česká republika, garant, domácí) a Lubomír POPELÍNSKÝ (203 Česká republika, domácí).
Vydání	NY, USA, IDEAS '14 Proceedings of the 18th International Database Engineering & Applications Symposium, od s. 294-297, 4 s. 2014.
Nakladatel	ACM New York

Další údaje
Originální jazyk	angličtina
Typ výsledku	Stať ve sborníku
Obor	10201 Computer sciences, information science, bioinformatics
Stát vydavatele	Spojené státy
Utajení	není předmětem státního či obchodního tajemství
Forma vydání	elektronická verze "online"
WWW	URL
Kód RIV	RIV/00216224:14330/14:00076180
Organizační jednotka	Fakulta informatiky
ISBN	978-1-4503-2627-8
Doi	http://dx.doi.org/10.1145/2628194.2628216
UT WoS	000471152000036
Klíčová slova anglicky	web mining;categorization of web pages;machine learning;landmarking
Změnil	Změnil: RNDr. Pavel Šmerk, Ph.D., učo 3880. Změněno: 5. 3. 2018 20:31.

Anotace
This paper introduces a new method for fast prototyping of web page categorization tool based on Random Forests. The result of this work is three-fold. We describe a fast feature extraction method first. Afterwards, we introduce a system that enables a user to perform experiments manually and visualize the results via visual analytics module. The last part of this work concerns a way how to perform experiments efficiently. It is partially inspired by landmarking that allows limiting the number of experiments. This method has been used for building a new commercial system for web categorization that significantly outperforms the system already being used.

Anotace

This paper introduces a new method for fast prototyping of web page categorization tool based on Random Forests. The result of this work is three-fold. We describe a fast feature extraction method first. Afterwards, we introduce a system that enables a user to perform experiments manually and visualize the results via visual analytics module. The last part of this work concerns a way how to perform experiments efficiently. It is partially inspired by landmarking that allows limiting the number of experiments. This method has been used for building a new commercial system for web categorization that significantly outperforms the system already being used.