Iryna (Hrsg.) Gurevych

The People's Web Meets NLP

Collaboratively Constructed Language Resources

Ebook (PDF Format)

Collaboratively Constructed Language Resources (CCLRs) such as Wikipedia, Wiktionary, Linked Open Data, and various resources developed using crowdsourcing techniques such as Games with a Purpose and Mechanical Turk have substantially contributed to the research in natural language processing (NLP). Various NLP tasks utilize such resources to substitute for or supplement conventional lexical semantic resources and linguistically annotated corpora. These resources also provide an extensive body of texts from which valuable knowledge is mined. There are an increasing number of community efforts to link and maintain multiple linguistic resources… Mehr

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Produktdetails

Weitere Autoren: Calzolari, Nicoletta (Vorb.) / Kim, Jungi (Hrsg.)

ISBN: 978-3-642-35085-6
EAN: 9783642350856
Produktnummer: 18257484
Verlag: Springer
Sprache: Englisch
Erscheinungsjahr: 2013
Seitenangabe: 378 S.
Plattform: PDF
Masse: 8'380 KB

Über den Autor

Iryna Gurevych leads the UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt (UKP-TUDA) and at the Institute for Educational Research and Educational Information (UKP-DIPF) in Frankfurt, Germany. She holds an endowed Lichtenberg-Chair Ubiquitous Knowledge Processing of the Volkswagen Foundation. Her research in NLP primarily concerns applied lexical semantic algorithms, such as computing semantic relatedness of words or paraphrase recognition, and their use to enhance the performance of NLP tasks, such as information retrieval, question answering, or summarization.Jungi Kim is a postdoctoral researcher at UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt, Germany (UKP-TUDA). His primary research interests are in semantic resources, algorithms, and evaluations for multilingual natural language processing. His previous research includes multilingual sentiment analysis, statistical machine translation, and various NLP topics involving multiple languages, especially East Asian languages.