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The Journal of Machine Learning Research
The Journal of Machine Learning Research
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ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Corpus-based Learning of Analogies and Semantic Relations
Machine Learning
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Computational Linguistics
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CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
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ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
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COLING-ACL '06 Proceedings of the COLING/ACL on Interactive presentation sessions
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ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
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AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
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ECML'06 Proceedings of the 17th European conference on Machine Learning
Annotating and learning compound noun semantics
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
Semantic classification with distributional kernels
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Using lexical and relational similarity to classify semantic relations
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
SemEval-2010 task 9: the interpretation of noun compounds using paraphrasing verbs and prepositions
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
SemEval-2010 task 9: The interpretation of noun compounds using paraphrasing verbs and prepositions
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Proceedings of the 1st international workshop on Search and mining entity-relationship data
Data & Knowledge Engineering
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ACM Transactions on Speech and Language Processing (TSLP) - Special issue on multiword expressions: From theory to practice and use, part 2
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Contextual information extracted from corpora is frequently used to model semantic similarity. We discuss distinct classes of context types and compare their effectiveness for compound noun interpretation. Contexts corresponding to word-word similarity perform better than contexts corresponding to relation similarity, even when relational co-occurrences are extracted from a much larger corpus. Combining word-similarity and relation-similarity kernels further improves SVM classification performance.