A vector space model for automatic indexing
Communications of the ACM
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Deep Read: a reading comprehension system
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Frequency estimates for statistical word similarity measures
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Corpus-based Learning of Analogies and Semantic Relations
Machine Learning
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Reading comprehension programs in a statistical-language-processing class
ANLP/NAACL-ReadingComp '00 Proceedings of the 2000 ANLP/NAACL Workshop on Reading comprehension tests as evaluation for computer-based language understanding sytems - Volume 6
A rule-based question answering system for reading comprehension tests
ANLP/NAACL-ReadingComp '00 Proceedings of the 2000 ANLP/NAACL Workshop on Reading comprehension tests as evaluation for computer-based language understanding sytems - Volume 6
A question answering system developed as a project in a natural language processing course
ANLP/NAACL-ReadingComp '00 Proceedings of the 2000 ANLP/NAACL Workshop on Reading comprehension tests as evaluation for computer-based language understanding sytems - Volume 6
A machine learning approach to answering questions for reading comprehension tests
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Dependency-Based Construction of Semantic Space Models
Computational Linguistics
Measuring the similarity between implicit semantic relations from the web
Proceedings of the 18th international conference on World wide web
A uniform approach to analogies, synonyms, antonyms, and associations
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Performance prediction for exponential language models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Shrinking exponential language models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
SemEval-2007 task 10: English lexical substitution task
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
FBK-irst: lexical substitution task exploiting domain and syntagmatic coherence
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
KU: word sense disambiguation by substitution
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UNT: SubFinder: combining knowledge sources for automatic lexical substitution
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Solving logic puzzles: from robust processing to precise semantics
TextMean '04 Proceedings of the 2nd Workshop on Text Meaning and Interpretation
Learning long-term dependencies with gradient descent is difficult
IEEE Transactions on Neural Networks
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This paper studies the problem of sentence-level semantic coherence by answering SAT-style sentence completion questions. These questions test the ability of algorithms to distinguish sense from nonsense based on a variety of sentence-level phenomena. We tackle the problem with two approaches: methods that use local lexical information, such as the n-grams of a classical language model; and methods that evaluate global coherence, such as latent semantic analysis. We evaluate these methods on a suite of practice SAT questions, and on a recently released sentence completion task based on data taken from five Conan Doyle novels. We find that by fusing local and global information, we can exceed 50% on this task (chance baseline is 20%), and we suggest some avenues for further research.