Assessing the Quality of Web Content

Elisabeth Lex; Inayat Khan; Horst Bischof; Michael Granitzer

Assessing the Quality of Web Content

Elisabeth Lex, Inayat Khan, Horst Bischof, Michael Granitzer

Research output: Contribution to journal › Article

Abstract

This paper describes our approach towards the ECML/PKDD Discovery Challenge 2010. The challenge consists of three tasks: (1) a Web genre and facet classification task for English hosts, (2) an English quality task, and (3) a multilingual quality task (German and French). In our approach, we create an ensemble of three classifiers to predict unseen Web hosts whereas each classifier is trained on a different feature set. Our final NDCG on the whole test set is 0:575 for Task 1, 0:852 for Task 2, and 0:81 (French) and 0:77 (German) for Task 3, which ranks second place in the ECML/PKDD Discovery Challenge 2010.

Original language	English
Journal	arXiv.org e-Print archive
Publication status	Published - 12 Jun 2014

Keywords

information quality
classification
machine learning
big data

ASJC Scopus subject areas

Computer Science(all)

Fields of Expertise

Information, Communication & Computing

Access to Document

pdf

Fingerprint Dive into the research topics of 'Assessing the Quality of Web Content'. Together they form a unique fingerprint.

Cite this

@article{69c98d954f794f96bf4ac5ec18dfb1c6,

title = "Assessing the Quality of Web Content",

abstract = "This paper describes our approach towards the ECML/PKDD Discovery Challenge 2010. The challenge consists of three tasks: (1) a Web genre and facet classification task for English hosts, (2) an English quality task, and (3) a multilingual quality task (German and French). In our approach, we create an ensemble of three classifiers to predict unseen Web hosts whereas each classifier is trained on a different feature set. Our final NDCG on the whole test set is 0:575 for Task 1, 0:852 for Task 2, and 0:81 (French) and 0:77 (German) for Task 3, which ranks second place in the ECML/PKDD Discovery Challenge 2010.",

keywords = "information quality, classification, machine learning, big data",

author = "Elisabeth Lex and Inayat Khan and Horst Bischof and Michael Granitzer",

note = "4 pages, ECML/PKDD 2010 Discovery Challenge Workshop",

year = "2014",

month = "6",

day = "12",

language = "English",

journal = "arXiv.org e-Print archive",

publisher = "Cornell University Library",

}

TY - JOUR

T1 - Assessing the Quality of Web Content

AU - Lex, Elisabeth

AU - Khan, Inayat

AU - Bischof, Horst

AU - Granitzer, Michael

N1 - 4 pages, ECML/PKDD 2010 Discovery Challenge Workshop

PY - 2014/6/12

Y1 - 2014/6/12

N2 - This paper describes our approach towards the ECML/PKDD Discovery Challenge 2010. The challenge consists of three tasks: (1) a Web genre and facet classification task for English hosts, (2) an English quality task, and (3) a multilingual quality task (German and French). In our approach, we create an ensemble of three classifiers to predict unseen Web hosts whereas each classifier is trained on a different feature set. Our final NDCG on the whole test set is 0:575 for Task 1, 0:852 for Task 2, and 0:81 (French) and 0:77 (German) for Task 3, which ranks second place in the ECML/PKDD Discovery Challenge 2010.

AB - This paper describes our approach towards the ECML/PKDD Discovery Challenge 2010. The challenge consists of three tasks: (1) a Web genre and facet classification task for English hosts, (2) an English quality task, and (3) a multilingual quality task (German and French). In our approach, we create an ensemble of three classifiers to predict unseen Web hosts whereas each classifier is trained on a different feature set. Our final NDCG on the whole test set is 0:575 for Task 1, 0:852 for Task 2, and 0:81 (French) and 0:77 (German) for Task 3, which ranks second place in the ECML/PKDD Discovery Challenge 2010.

KW - information quality

KW - classification

KW - machine learning

KW - big data

M3 - Article

JO - arXiv.org e-Print archive

JF - arXiv.org e-Print archive

ER -