Assessing the Quality of Web Content

2014/06/12 by Elisabeth Lex, Inayatullah Khan, Lex, Elisabeth +5
Computer Science · #Authorship Attribution and Profiling #D.2.8 #FOS: Computer and information sciences #H.4 #Information Retrieval (cs.IR) #Natural Language Processing Techniques #Topic Modeling

paper · pdf · doi:10.48550/arxiv.1406.3188

openalex publication_date 2014/06/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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