Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Using discourse commitments to recognize textual entailment
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Bootstrapping distributional feature vector quality
Computational Linguistics
Augmenting WordNet for deep understanding of text
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
Inferring textual entailment with a probabilistically sound calculus*
Natural Language Engineering
Assessing the impact of frame semantics on textual entailment
Natural Language Engineering
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
Machine learning based semantic inference: experiments and observations at RTE-3
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
Studying the influence of semantic constraints in AVE
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Assessing the role of discourse references in entailment inference
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
DLSITE-1: lexical analysis for solving textual entailment recognition
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
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This paper presents two systems for textual entailment, both employing decision trees as a supervised learning algorithm. The first one is based primarily on the concept of lexical overlap, considering a bag of words similarity overlap measure to form a mapping of terms in the hypothesis to the source text. The second system is a lexico-semantic matching between the text and the hypothesis that attempts an alignment between chunks in the hypothesis and chunks in the text, and a representation of the text and hypothesis as two dependency graphs. Their performances are compared and their positive and negative aspects are analyzed.