recognising nested named entities in biomedical text

... substances and findings have special affixes, which are very distinguishable from ordinary words. Lexical Features: Every token in the training data was used as a feature. Alphabetic words in the training data ... are only used once. The clinical information extraction problem is addressed in this work by applying machine learn- ing methods to a corpus annotated for clinical named entities. The data selection ... 2003. Towards link- ing patients and clinical information: detecting UMLS concepts in e-mail. Journal of Biomedical Informatics,36(4/5),334–341. A. C ˆ ot ´ e and American Veterinary Medical Associa- tion...

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Ngày tải lên: 17/03/2014, 04:20

... 2010. Annotating named entities in twitter data with crowd- sourcing. In CSLDAMT, pages 80–88. Jenny Rose Finkel and Christopher D. Manning. 2009. Nested named entity recognition. In EMNLP, pages 141–150. Jenny ... 2009. Annotating and recognising named entities in clinical notes. In ACL-IJCNLP, pages 18– 26. Dan Wu, Wee Sun Lee, Nan Ye, and Hai Leong Chieu. 2009. Domain adaptive bootstrapping for named en- tity ... transcripts. In EMNLP, pages 320–327. Jing Jiang and ChengXiang Zhai. 2007. Instance weight- ing for domain adaptation in nlp. In ACL, pages 264– 271. Dan Klein and Christopher D. Manning. 2003....

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... previously seen in the training corpus, and therefore their overall coverage is not 100%. Starting with an annotated corpus consisting of all annotated files in SemCor, a separate training data set is ... Min- imally supervised word sense disambiguation for all words in open text. In Proceedings of ACL/SIGLEX Senseval-3, Barcelona, Spain, July. R. Mihalcea and D. Moldovan. 2002. Pattern learning and ... vectors constructed in this learn- ing stage for each semantic model. To annotate new text, similar vectors are created for all content-words in the raw text. Similar to the train- ing stage, feature...

Ngày tải lên: 20/02/2014, 15:20

... 2000. Mapping wordnets using structural information. In Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics, Hong Kong. Finding Predominant Word Senses in Untagged ... BNC text represents imaginative writing, the remaining 80% being classified as informative. sense according to SemCor. This seems intuitive given our expected relative usage of these senses in modern ... word sense disam- biguation using WordNet. In Proceedings of the Third International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-02), Mexico City. Edward Briscoe...

Ngày tải lên: 20/02/2014, 16:20

... Cambridge, MA. 450 Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line 1234567890123456789012345678901234567890123456789012345678901234567890 ... Computational Lin- guistics, pages 19-24. Shona Douglas, Matthew Hurst, and David Quinn. 1995. Using natural language processing for iden- tifying and interpreting tables in plain text. In Fourth ... blank lines or delimiters that immediately precede or follow a table within an input text. In this paper, we assume that our input texts are plain texts that do not contain any formatting codes,...

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... Webber's rules to detect modal and other index-binding contexts. In representing DEs for indefinites (appearing as existential formulae in our meaning representation), we replaced Webber's ... DEs originating from non-linguistic sources, such as pointing actions, were taken into account. The discourse entities are used in intra- and extra-sentential pronoun resolution in BBN Janus. ... for generating DEs for dependent quantifiers stemming from indefinite and definite NPs which over- comes some difficulties in capturing dependencies be- tween discourse entities. In our multi-modal...

Ngày tải lên: 21/02/2014, 20:20

... Vector Space Model (VSM) in text information processing, document indexing (term extraction) acts as a pre-requisite step in most text information proc- essing tasks such as Information Retrieval ... Intelligent Text Processing (CI- CLing 2003), 602-614. Yuan Liu, Nanyuan Liang. 1986. Basic Engineering for Chinese Processing – Contemporary Chinese Words Frequency Count, Journal of Chinese In- formation ... Xiaojing Bai, Shiwen Yu. 2003. Experimental Study on Representing Units in Chinese Text Categorization, Proceedings of the 4 th International Conference on Computational Linguistics and Intelligent...

Ngày tải lên: 08/03/2014, 02:21

... principles of reasoning with uncertainty: e.g. Connoly (1994) and Mitkov (1997). Our system can be included into the first approach. In these integrated approaches the semantic and domain ... worked on different texts (Spanish texts). apply a partial parsing and we deal with other kinds of anaphors. As a future aim we will include semantic information in our algorithm in order to check ... which includes all the coordinated noun phrases (in this case John and Bill). We will detect the coordination of noun phrases from the SS returned by the SUG fact coordinated. In one- 4 In...

Ngày tải lên: 08/03/2014, 05:21

... part of the FBIS 2001 Multilingual corpus. Translating Named Entities Using Monolingual and Bilingual Resources Yaser Al-Onaizan and Kevin Knight Information Sciences Institute University of Southern ... becausemany are domain specific, not to be found in bilingual dictionaries. We present a novel algorithm for translating named entity phrases using easily obtain- able monolingual and bilingual resources. We ... to iden- tify all named entities in the top retrieved docu- ments for each sub-phrase. All named entities of the type of the named entity in question (e.g., PER- SON) foundin the retrieved documents...

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