cc_project_author,post_title,cc_project_url,cc_project_category,post_date,keywords,abstract,cc_author_affiliation,cc_class,cc_snippet,cc_dataset_used,cc_derived_dataset_about,cc_derived_dataset_used,cc_derived_dataset_cited
"Ivan Habernal, Omnia Zayed, Iryna Gurevych – University of Darmstadt, Germany",C4Corpus: Multilingual Web-Size Corpus with Free License,http://www.lrec-conf.org/proceedings/lrec2016/pdf/388_Paper.pdf,papers,20160101Z00:00:00,,"Large Web corpora containing full documents with permissive licenses are crucial for many NLP tasks. In this article we present the construction of 12 million-pages Web corpus (over 10 billion tokens) licensed under CreativeCommons license family in 50+ languages that has been extracted from CommonCrawl, the largest publicly available general Web crawl to date with about 2 billion crawled URLs. Our highly-scalable Hadoop-based framework is able to process the full CommonCrawl corpus on 2000+ CPU cluster on the Amazon Elastic Map/Reduce infrastructure. The processing pipeline includes license identification, state-of-the-art boilerplate removal, exact duplicate and near-duplicate document removal, and language detection. The construction of the corpus is highly configurable and fully reproducible, and we provide both the framework (DKPro C4CorpusTools) and the resulting data (C4Corpus) to the research community.","University of Darmstadt, Germany","nlp/corpus-construction, legal/copyright, license/creative-commons, nlp/boilerplate-removal, ir/duplicate-detection",,CC-MAIN-2016-07,{DKPro-C4},,
"Roland Schäfer – Freie Universität Berlin, Germany",CommonCOW: Massively Huge Web Corpora from CommonCrawl Data and a Method to Distribute them Freely under Restrictive EU Copyright Laws,http://rolandschaefer.net/?p=994,papers,20160101Z00:00:00,,"In this paper, I describe a method of creating massively huge web corpora from the CommonCrawl data sets and redistributing the resulting annotations in a stand-off format. Current EU (and especially German) copyright legislation categorically forbids the redistribution of downloaded material without express prior permission by the authors. Therefore, stand-off annotations or other derivates are the only format in which European researchers (like myself) are allowed to re-distribute the respective corpora. In order to make the full corpora available to the public despite such restrictions, the stand-off format presented here allows anybody to locally reconstruct the full corpora with the least possible computational effort.","Freie Universität Berlin, Germany","nlp/corpus-construction, legal/copyright",,,{CommonCOW},,