Two biomedical sublanguages: a description based on the theories of Zellig Harris
Journal of Biomedical Informatics - Special issue: Sublanguage
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
Journal of Biomedical Informatics - Special issue: Unified medical language system
Journal of the American Society for Information Science and Technology - Bioinformatics
MedPost: a part-of-speech tagger for bioMedical text
Bioinformatics
Postnominal prepositional phrase attachment in proteomics
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Overview of BioNLP'09 shared task on event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
High-precision biological event extraction with a concept recognizer
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Syntactic dependency based heuristics for biological event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Abstraction summarization for managing the biomedical research literature
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
Semantic role assignment for event nominalisations by leveraging verbal data
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Semantic Role Labeling of NomBank: a maximum entropy approach
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Parsing arguments of nominalizations in English and Chinese
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Journal of Biomedical Informatics
Mining of parsed data to derive deverbal argument structure
GEAF '09 Proceedings of the 2009 Workshop on Grammar Engineering Across Frameworks
Semantic interpretation of nominalizations
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Combining semantic relations and DNA microarray data for novel hypotheses generation
ISMB/ECCB'09 Proceedings of the 2009 workshop of the BioLink Special Interest Group, international conference on Linking Literature, Information, and Knowledge for Biology
Building frame-based corpus on the basis of ontological domain knowledge
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Finding schizophrenia's Prozac: emergent relational similarity in predication space
QI'11 Proceedings of the 5th international conference on Quantum interaction
Ontology-Driven construction of domain corpus with frame semantics annotations
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Discovering discovery patterns with predication-based Semantic Indexing
Journal of Biomedical Informatics
Automatic Identification and Classification of Noun Argument Structures in Biomedical Literature
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Many paths lead to discovery: analogical retrieval of cancer therapies
QI'12 Proceedings of the 6th international conference on Quantum Interaction
UAHCI'13 Proceedings of the 7th international conference on Universal Access in Human-Computer Interaction: applications and services for quality of life - Volume Part III
Development and evaluation of a biomedical search engine using a predicate-based vector space model
Journal of Biomedical Informatics
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Based on linguistic generalizations, we enhanced an existing semantic processor, SemRep, for effective interpretation of a wide range of patterns used to express arguments of nominalization in clinically oriented biomedical text. Nominalizations are pervasive in the scientific literature, yet few text mining systems adequately address them, thus missing a wealth of information. We evaluated the system by assessing the algorithm independently and by determining its contribution to SemRep generally. The first evaluation demonstrated the strength of the method through an F-score of 0.646 (P=0.743, R=0.569), which is more than 20 points higher than the baseline. The second evaluation showed that overall SemRep results were increased to F-score 0.689 (P=0.745, R=0.640), approximately 25 points better than processing without nominalizations.