Computational Linguistics
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SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Natural language processing and knowledge representation
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The Journal of Machine Learning Research
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COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
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ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
ACM SIGKDD Explorations Newsletter
Using the web to overcome data sparseness
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning non-taxonomic relationships from web documents for domain ontology construction
Data & Knowledge Engineering
Ontology-driven, unsupervised instance population
Web Semantics: Science, Services and Agents on the World Wide Web
Automatic Acquisition of Qualia Structure from Corpus Data
IEICE - Transactions on Information and Systems
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Proceedings of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge
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International Journal of Metadata, Semantics and Ontologies
Automatic identification of semantic relations in Italian complex nominals
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
Forgive and forget: return to obscurity
Proceedings of the 2013 workshop on New security paradigms workshop
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Qualia Structures have many applications within computational linguistics, but currently there are no corresponding lexical resources such as WordNet or FrameNet. This paper presents an approach to automatically learn qualia structures for nominals from the World Wide Web and thus opens the possibility to explore the impact of qualia structures for natural language processing at a larger scale. Furthermore, our approach can be also used support a lexicographer in the task of manually creating a lexicon of qualia structures. The approach is based on the idea of matching certain lexico-syntactic patterns conveying a certain semantic relation on the World Wide Web using standard search engines. We evaluate our approach qualitatively by comparing our automatically learned qualia structures with the ones from the literature, but also quantitatively by presenting results of a human evaluation.