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Computer Science - Artificial Intelligence | Language Technology for Cultural Heritage - Selected Papers from the LaTeCH Workshop Series (Authors and Editors)

Language Technology for Cultural Heritage

Selected Papers from the LaTeCH Workshop Series

Sporleder, Caroline, van den Bosch, Antal, Zervanou, Kalliopi (Eds.)

2011, XXXII, 232 p.

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Caroline Sporleder leads a junior research group in the Cluster of Excellence “Multimodal Computing and Interaction” at Saarland University, Germany. Her research interests include text mining and error detection for cultural heritage data, cross-domain language processing, and computational modelling of semantics and discourse. Before coming to Saarland University, she worked as a post-doctoral researcher on the MITCH project (Mining for Information from the Cultural Heritage), a joint research project between Tilburg University, and Naturalis, the Dutch National Museum of Natural History. The project aimed at developing technology to clean, enrich and structure field books and other natural history data sources.

Antal van den Bosch is a full professor of computational linguistics and artificial intelligence at Tilburg University. His research interests include machine learning of natural language; historical and heritage text mining; proofing and recommendation; and machine translation. He helped create the Dutch CATCH programme (Continuous Access to Cultural Heritage) funded by the Netherlands Organization for Scientific Research, and has been PI of two CATCH projects: the aforementioned MITCH (with Caroline Sporleder) and the current HitiMe project (with Kalliopi Zervanou). He was guest editor of the special issue of the Interdisciplinary Science Review journal on “Continuous access to cultural heritage” published in 2009.

Kalliopi A. Zervanou is a post-doctoral researcher in the HiTiME project (Historical Timeline Mining and Extraction), a joint research project by Tilburg University’s Centre for Cognition and Communication (TiCC) and the International Institute of Social History. The project aims at the development of a text analysis system for the recognition and extraction of historical events and facts from a variety of primary and secondary historical sources. Previous to HiTiME, she worked as a researcher at the University of Manchester, and the Technical University of Crete, in various information management and text mining projects. Her research interests include information extraction, knowledge acquisition and representation techniques, automatic term extraction and abstracting.

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