A non-projective dependency parser
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Similarity-based methods for word sense disambiguation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Using syntactic dependency as local context to resolve word sense ambiguity
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Computer-aided generation of multiple-choice tests
HLT-NAACL-EDUC '03 Proceedings of the HLT-NAACL 03 workshop on Building educational applications using natural language processing - Volume 2
A computer-aided environment for generating multiple-choice test items
Natural Language Engineering
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Extended gloss overlaps as a measure of semantic relatedness
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Using measures of semantic relatedness for word sense disambiguation
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Automatic distractor generation for domain specific texts
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Simplify or help?: text simplification strategies for people with dyslexia
Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility
Dyslexia exercises on my tablet are more fun
Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility
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Mitkov and Ha (2003) and Mitkov et al. (2006) offered an alternative to the lengthy and demanding activity of developing multiple-choice test items by proposing an NLP-based methodology for construction of test items from instructive texts such as textbook chapters and encyclopaedia entries. One of the interesting research questions which emerged during these projects was how better quality distractors could automatically be chosen. This paper reports the results of a study seeking to establish which similarity measures generate better quality distractors of multiple-choice tests. Similarity measures employed in the procedure of selection of distractors are collocation patterns, four different methods of WordNet-based semantic similarity (extended gloss overlap measure, Leacock and Chodorow's, Jiang and Conrath's as well as Lin's measures), distributional similarity, phonetic similarity as well as a mixed strategy combining the aforementioned measures. The evaluation results show that the methods based on Lin's measure and on the mixed strategy outperform the rest, albeit not in a statistically significant fashion.