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We present a new approach to cross-language text classification that builds on structural correspondence learning, a recently proposed theory for domain adaptation. The approach uses unlabeled documents , along with a simple word translation oracle, in order to induce task-specific, cross-lingual word correspondences. We report on analyses that reveal(More)
We address the problem of query segmentation: given a keyword query, the task is to group the keywords into phrases, if possible. Previous approaches to the problem achieve reasonable segmentation performance but are tested only against a small corpus of manually segmented queries. In addition, many of the previous approaches are fairly intricate as they(More)
We present an evaluation framework for plagiarism detection. 1 The framework provides performance measures that address the specifics of plagiarism detection , and the PAN-PC-10 corpus, which contains 64 558 artificial and 4 000 simulated plagiarism cases, the latter generated via Amazon's Mechanical Turk. We discuss the construction principles behind the(More)
For the identification of plagiarized passages in large document collections we present retrieval strategies which rely on stochastic sampling and chunk indexes. Using the entire Wikipedia corpus we compile n-gram indexes and compare them to a new kind of fingerprint index in a plagiarism analysis use case. Our index provides an analysis speed-up by factor(More)
Cross-language plagiarism detection deals with the automatic identification and extraction of plagiarism in a multilingual setting. In this setting, a suspicious document is given, and the task is to retrieve all sections from the document that originate from a large, multilingual document collection. Our contributions in this field are as follows: (i) a(More)
This paper reports on the PAN 2014 evaluation lab which hosts three shared tasks on plagiarism detection, author identification, and author profiling. To improve the reproducibility of shared tasks in general, and PAN's tasks in particular , the Webis group developed a new web service called TIRA, which facilitates software submissions. Unlike many other(More)