The nature of statistical learning theory
The nature of statistical learning theory
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
The PASCAL recognising textual entailment challenge
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
Recognizing textual entailment using a machine learning approach
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
A statistics-based semantic textual entailment system
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on RITE
An investigation into the application of ensemble learning for entailment classification
Information Processing and Management: an International Journal
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This paper describes our experiments on Textual Entailment in the context of the Third Pascal Recognising Textual Entailment (RTE-3) Evaluation Challenge. Our system uses a Machine Learning approach with Support Vector Machines and AdaBoost to deal with the RTE challenge. We perform a lexical, syntactic, and semantic analysis of the entailment pairs. From this information we compute a set of semantic-based distances between sentences. The results look promising specially for the QA entailment task.