Extracting shallow paraphrasing schemata from modern Greek text using statistical significance testing and supervised learning

Authors:
Katia Lida Kermanidis
Affiliations:
Department of Informatics, Ionian University, Corfu, Greece
Venue:
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
Year:
2010

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Abstract

Paraphrasing normally involves sophisticated linguistic resources for pre-processing. In the present work Modern Greek paraphrases are automatically generated using statistical significance testing in a novel manner for the extraction of applicable reordering schemata of syntactic constituents. Next, supervised filtering helps remove erroneously generated paraphrases, taking into account the context surrounding the reordering position. The proposed process is knowledge-poor, and thus portable to languages with similar syntax, robust and domain-independent. The intended use of the extracted paraphrases is hiding secret information underneath a cover text.