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THIS RESOURCE IS NO LONGER AVAILABLE. Documented September 18, 2017

Text Mining platform that copes with major Information Retrieval and Information Extraction tasks and promotes multi-disciplinary research. It aims to provide support to three different usage roles: biologists, text miners and application developers. The workbench supports the retrieval, processing and annotation of documents as well as their analysis at different levels.


Keywords

java, java swt

Resource ID

SCR_005342

Alternate IDs

OMICS_01167

Website Status

Last checked up

Abbreviation(s)

(at)Note

Resource Type

Resource, software resource, software application, text-mining software

Availability

THIS RESOURCE IS NO LONGER AVAILABLE, Acknowledgement requested, GNU General Public License, v3 or later

Synonym(s)

(at)Note2 - A workbench for Biomedical Text Mining

Proper citation

((at)Note, RRID:SCR_005342)

Reference

PMID:19393341

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Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch are assigned RRIDs which are used to cite resources in scientific manuscripts.

@Note: a workbench for biomedical text mining.

  • Lourenço A
  • J Biomed Inform
  • 2009 Aug 6

Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature. However, most efforts have addressed the benchmarking of new algorithms rather than user operational needs. Bridging the gap between BioTM researchers and biologists' needs is crucial to solve real-world problems and promote further research. We present @Note, a platform for BioTM that aims at the effective translation of the advances between three distinct classes of users: biologists, text miners and software developers. Its main functional contributions are the ability to process abstracts and full-texts; an information retrieval module enabling PubMed search and journal crawling; a pre-processing module with PDF-to-text conversion, tokenisation and stopword removal; a semantic annotation schema; a lexicon-based annotator; a user-friendly annotation view that allows to correct annotations and a Text Mining Module supporting dataset preparation and algorithm evaluation. @Note improves the interoperability, modularity and flexibility when integrating in-home and open-source third-party components. Its component-based architecture allows the rapid development of new applications, emphasizing the principles of transparency and simplicity of use. Although it is still on-going, it has already allowed the development of applications that are currently being used.

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