Cross-language information retrieval with the UMLS metathesaurus
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Question-answering by predictive annotation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Real-time texture synthesis by patch-based sampling
ACM Transactions on Graphics (TOG)
Journal of Biomedical Informatics - Special issue: Unified medical language system
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Generic soft pattern models for definitional question answering
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Abstraction summarization for managing the biomedical research literature
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
Customization in a unified framework for summarizing medical literature
Artificial Intelligence in Medicine
Automatically generating extraction patterns from untagged text
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Journal of Biomedical Informatics
Biomedical question answering: A survey
Computer Methods and Programs in Biomedicine
Automatically extracting information needs from complex clinical questions
Journal of Biomedical Informatics
Hi-index | 0.00 |
Most current definitional question answering systems apply one-size-fits-all lexicosyntactic patterns to identify definitions. By analyzing a large set of online definitions, this study shows that the semantic types of definienda constrain both lexical semantics and lexicosyntactic patterns of the definientia. For example, "heart" has the semantic type [Body Part, Organ, or Organ Component] and its definition (e.g., "heart locates between the lungs") incorporates semantic-type-dependent lexicosyntactic patterns (e.g., "TERM locates ...") and terms (e.g., "lung" has the same semantic type [Body Part, Organ, or Organ Component]). In contrast, "AIDS" has a different semantic type [Disease or Syndrome]; its definition (e.g., "An infectious disease caused by human immunodeficiency virus") consists of different lexicosyntactic patterns (e.g., "...causes by...") and terms (e.g., "infectious disease" has the semantic type [Disease or Syndrome]). The semantic types are defined in the widely used biomedical knowledge resource, the Unified Medical Language System (UMLS).