Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Corpus-based Learning of Analogies and Semantic Relations
Machine Learning
Out-of-context noun phrase semantic interpretation with cross-linguistic evidence
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Using the web as an implicit training set: application to structural ambiguity resolution
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Models for the semantic classification of noun phrases
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
Using verbs to characterize noun-noun relations
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
A knowledge-rich approach to identifying semantic relations between nominals
Information Processing and Management: an International Journal
Using local alignments for relation recognition
Journal of Artificial Intelligence Research
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For our system we use the SMO implementation of a support vector machine provided with the WEKA machine learning toolkit. As with all machine learning approaches, the most important step is to choose a set of features which reliably help to predict the label of the example. We used 76 features drawn from two very different knowledge sources. The first 48 features are boolean values indicating whether or not each of the nominals in the sentence are linked to certain other words in the WordNet hypernym and meronym networks. The remaining 28 features are web frequency counts for the two nominals joined by certain common prepositions and verbs. Our system performed well on all but two of the relations; theme-tool and origin entity.