Bringing Named Entity Recognition on Drupal Content Management System

  • José FerrnandesEmail author
  • Anália Lourenço
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 294)


Content management systems and frameworks (CMS/F) play a key role in Web development. They support common Web operations and provide for a number of optional modules to implement customized functionalities. Given the increasing demand for text mining (TM) applications, it seems logical that CMS/F extend their offer of TM modules. In this regard, this work contributes to Drupal CMS/F with modules that support customized named entity recognition and enable the construction of domain-specific document search engines. Implementation relies on well-recognized Apache Information Retrieval and TM initiatives, namely Apache Lucene, Apache Solr and Apache Unstructured Information Management Architecture (UIMA). As proof of concept, we present here the development of a Drupal CMS/F that retrieves biomedical articles and performs automatic recognition of organism names to enable further organism-driven document screening.


Drupal text mining named entity recognition Apache Lucene Apache Solr Apache UIMA 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.ESEI - Escuela Superior de Ingeniería Informática, Edificio PolitécnicoUniversity of VigoOurenseSpain
  2. 2.IBB - Institute for Biotechnology and Bioengineering, Centre of Biological EngineeringUniversity of MinhoBragaPortugal

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