GATE

GATE: In this paper we present GATE, a framework and graphical development environment which enables users to develop and deploy language engineering components and resources in a robust fashion. The GATE architecture has enabled us not only to develop a number of successful applications for various language processing tasks (such as Information Extraction), but also to build and annotate corpora and carry out evaluations on the applications generated. The framework can be used to develop applications and resources in multiple languages, based on its thorough Unicode support.


References in zbMATH (referenced in 14 articles )

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  1. Xu, Kaiquan; Liao, Stephen Shaoyi; Lau, Raymond Y. K.; Leon Zhao, J.: Effective active learning strategies for the use of large-margin classifiers in semantic annotation: an optimal parameter discovery perspective (2014)
  2. Abreu, Pedro Henriques; Moura, José; Silva, Daniel Castro; Reis, Luís Paulo; Garganta, Júlio: Performance analysis in soccer: a Cartesian coordinates based approach using RoboCup data (2012) ioport
  3. Gleich, David F.; Wang, Ying; Meng, Xiangrui; Ronaghi, Farnaz; Gerritsen, Margot; Saberi, Amin: Some computational tools for digital archive and metadata maintenance (2011)
  4. Li, Lei; Wang, Ding-Ding; Zhu, Shun-Zhi; Li, Tao: Personalized news recommendation: a review and an experimental investigation (2011) ioport
  5. López, Claudia; Codocedo, Víctor; Astudillo, Hernán; Cysneiros, Luiz Marcio: Bridging the gap between software architecture rationale formalisms and actual architecture documents: an ontology-driven approach (2011) ioport
  6. Rudin, Cynthia; Passonneau, Rebecca J.; Radeva, Axinia; Dutta, Haimonti; Ierome, Steve; Isaac, Delfina: A process for predicting manhole events in Manhattan (2010) ioport
  7. Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco: A bioinformatics knowledge discovery in text application for grid computing (2009) ioport
  8. Lugmayr, Artur; Risse, Thomas; Stockleben, Bjoern; Laurila, Kari; Kaario, Juha: Semantic ambient media-an introduction (2009) ioport
  9. Ingo Feinerer; Kurt Hornik; David Meyer: Text Mining Infrastructure in R (2008) not zbMATH
  10. Richardson, W. Ryan; Srinivasan, Venkat; Fox, Edward A.: Knowledge discovery in digital libraries of electronic theses and dissertations: An NDLTD case study (2008) ioport
  11. Zhang, Zhu: Mining relational data from text: From strictly supervised to weakly supervised learning (2008) ioport
  12. Nguyen, Truc-Vien T.; Cao, Tru H.: VN-KIM IE: automatic extraction of Vietnamese named-entities on the Web (2007) ioport
  13. Recupero, Diego Reforgiato: A new unsupervised method for document clustering by using WordNet lexical and conceptual relations (2007) ioport
  14. Baker, Christopher J. O.; Witte, René: Mutation mining-A prospector’s tale (2006) ioport