Paper: Paraphrase Recognition Using Machine Learning to Combine Similarity Measures

ACL ID P09-3004
Title Paraphrase Recognition Using Machine Learning to Combine Similarity Measures
Venue ACL-IJCNLP: Student Research Workshop papers
Session
Year 2009
Authors

This paper presents three methods that can be used to recognize paraphrases. They all employ string similarity measures ap- plied to shallow abstractions of the input sentences, and a Maximum Entropy clas- sifier to learn how to combine the result- ing features. Two of the methods also ex- ploit 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 cor- pus. Our system achieves state of the art or better results.