Shallow Morphological Analysis in Monolingual Information Retrieval for Dutch, German, and Italian
CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Automatic translation of noun compounds
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 4
Empirical methods for compound splitting
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Decompounding query keywords from compounding languages
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Data-driven compound splitting method for english compounds in domain names
Proceedings of the 18th ACM conference on Information and knowledge management
Language-independent compound splitting with morphological operations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Recursive decompounding in Afrikaans
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Algorithms for the verification of the semantic relation between a compound and a given lexeme
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
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Splitting compound words has proved to be useful in areas such as Machine Translation, Speech Recognition or Information Retrieval (IR). In the case of IR systems, they usually have to cope with noisy data, as user queries are usually written quickly and submitted without review. This work attempts at improving the current approaches for German decompounding when applied to query keywords. The results show an increase of more than 10% in accuracy compared to other state-of-the-art methods.