Paraphrase Recognition Using Machine Learning to Combine Similarity Measures

This paper presents three methods that can be used to recognize paraphrases. They all employ string similarity measures apshallow abstractions of the input sentences, and a Maximum Entropy classifier to learn how to combine the resulting features. Two of the methods also exploit WordNet to detect synonyms and one of them also exploits a dependency parser. We experiment on two datasets, the MSR paraphrasing corpus and a dataset that we automatically created from the MTC corpus. Our system achieves state of the art or better results.

• Type: Journal
• Year: 2009
• Where: ACL
• Authors: Prodromos Malakasiotis
• Keywords: ACL 2009, Computational Linguistics, Employ String, Maximum Entropy Classifier, Similarity Measures