Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Discovering corpus-specific word senses
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Semiautomatic labelling of semantic features
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Domain kernels for word sense disambiguation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Personalizing PageRank for word sense disambiguation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
Semantic similarity of distractors in multiple-choice tests: extrinsic evaluation
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
ArikIturri: an automatic question generator based on corpora and NLP techniques
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Generating diagnostic multiple choice comprehension cloze questions
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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This paper presents a system which uses Natural Language Processing techniques to generate multiple-choice questions. The system implements different methods to find distractors semantically similar to the correct answer. For this task, a corpus-based approach is applied to measure similarities. The target language is Basque and the questions are used for learners' assessment in the science domain. In this article we present the results of an evaluation carried out with learners to measure the quality of the automatically generated distractors.