Marco Trevisan


2013

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Celi: EDITS and Generic Text Pair Classification
Milen Kouylekov | Luca Dini | Alessio Bosca | Marco Trevisan
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)

2012

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Query log analysis with LangLog
Marco Trevisan | Eduard Barbu | Igor Barsanti | Luca Dini | Nikolaos Lagos | Frédérique Segond | Mathieu Rhulmann | Ed Vald
Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics

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CELI: An Experiment with Cross Language Textual Entailment
Milen Kouylekov | Luca Dini | Alessio Bosca | Marco Trevisan
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)

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Linguagrid: a network of Linguistic and Semantic Services for the Italian Language.
Alessio Bosca | Luca Dini | Milen Kouylekov | Marco Trevisan
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

In order to handle the increasing amount of textual information today available on the web and exploit the knowledge latent in this mass of unstructured data, a wide variety of linguistic knowledge and resources (Language Identification, Morphological Analysis, Entity Extraction, etc.). is crucial. In the last decade LRaas (Language Resource as a Service) emerged as a novel paradigm for publishing and sharing these heterogeneous software resources over the Web. In this paper we present an overview of Linguagrid, a recent initiative that implements an open network of linguistic and semantic Web Services for the Italian language, as well as a new approach for enabling customizable corpus-based linguistic services on Linguagrid LRaaS infrastructure. A corpus ingestion service in fact allows users to upload corpora of documents and to generate classification/clustering models tailored to their needs by means of standard machine learning techniques applied to the textual contents and metadata from the corpora. The models so generated can then be accessed through proper Web Services and exploited to process and classify new textual contents.